From environmentalist Jennifer Marohasy’s blog in Australia, please pay her a visit here – Anthony
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/
Cool!
The phrase “Don’t pee on my back and tell me it’s raining” comes to mind.
Thank you Michael Hammer and Anthony for presenting this revealing analysis of NOAA’s adjustments. It is valuable in as much as it comes from an offshore viewpoint of our governments manipulations of the data to match the AGW agenda. Our current government seems not to care about the facts but hopefully we the public do. Let your elected officials know how you feel and if they are unwilling to represent you then vote them out.
I brought up many of the same issues in my March report, I’m pleased to see somebody is looking at them.
“click for larger image” doesn’t work for 1st figure.
FIXED- thanks, Anthony
I got it to work. Try again, perhaps?
Wow, what are the odds that I would happen upon this right as the link got fixed? Why I can’t I be in the right place at the right time buying my one lottery ticket a month? Sheesh.
Just sent this to John Boehner, who has some “interesting” discussions of the current Waxman/Markey “screw America” “climate change” bill here.
If the surface data is no one say fraudulent, do we assume that the satellite data was ‘calibrated’ against adjusted surface data thus polluting all global temperature datasets?
Some time ago I had reason to look at temps in the US.
My thought with this graph (using NCDC / NOAA’s own tools) was that during the early decades of the 20th century we not done exiting out of the LIA. So I selected 1920 as a start point. Then the big warming bomb from the IPCC …. 1995. So, what was happening in the US during that course of 75 years? A much longer period than the favored 30 – 40 year span used by many.
Was the US in concert with the rest of the world? After all we span a fairly large land area, we contain many types of geographical terrain, we span more than 20 degrees of latitude, and the country has great diversity in regional climate conditions. A good sampling.
In a straight, simple, linear regression what was the amount of warming? .5 C ? .6 C ?
This is what the results were:
http://penoflight.com/climatebuzz/Files/UStemp3.jpg
If you note; the data started in 1921 and not 1920 (20 was cooler than 21). So, I did it again AND added 2 years taking it to 1997 and right up against the 1998 El Nino anomaly.
This was the result of that set;
http://www.penoflight.com/climatebuzz/Files/temp2097.jpg
I should take that data and create my own graph and incorporate CO2 data as well…. just for the sake of doing so.
Because of all of the concerns about air temperature, alternative measures of temperature become important. Articles in press in a special issue of Limnology and Oceanography show that the water temperatures of nearly all of the large lakes in Europe and North America with long term data show relatively consistent rises in temperature over the last 25-50 years that match reported changes in air temperature. Many of these lakes, such as Lake Washington (Seattle) and Lake Zurich (Switzerland) have towns or cities on their shores. While human populations can cause increases in pollution, no one has claimed that Urban heat effects can influence the temperature of large lakes. Moreover, the same trends are seen in lakes with less human development. While there are valid concerns about Urban heat effects that should be investigated by statistical analysis, the lake data show that temperature increases over the past 3-5 decades are real and quite in line with the surface temperature record.
It is my understanding that the time of day observation adjustment (TOBS) is non controversial. I think Anthony Watts confirmed this once. What does the data look like if the TOBS adjustment is left in.
Shane
I’ve often wondered, prior to satellite data, what was the method of determining global temperature since vast areas of ocean (I would assume) had little or no temperature data. Hansen downplays the area of the USA (when it comes to say, the 1930s records) But should not this information (necessarily) be used to estimate temperatures over a larger area, and if yes, what is the method?
What we see in Fig 5 is precisely what has been my sneaking suspicion from the outset: That we’ve probably never again reached the temps of the 30’s/40’s.
Sorry but I find Mike’s riff misleading. I too want to look into the adjustment procedures, but it is not appropriate to claim that you are getting the “raw” data by subtracting NOAA’s USHCN from GISS GLOBAL Data.
And as some have already said, some of the adjustments might well be reasonable. We need a thorough analysis sort it out, but this hardly rises to that level.
There has been further adjustments done to USHCN in the new Version 2.
The total adjustments are now about 0.425C or 0.765F (from about 1920).
The (different method) of adjustments in USHCNV2 can be seen in Figure 4 (page 41) and Figure 7 (page 44) here. [There is one other set of adjustments Figure 10 (page 47) but there is no net change from this adjustment].
http://ams.allenpress.com/archive/1520-0477/preprint/2009/pdf/10.1175_2008BAMS2613.1.pdf
The adjustments are shown as their separate impact on Minimum temps and Maximum temps but one can just do the math.
———-
In terms of whether the TOBs adjustment is valid or not, it depends entirely on how it was implemented.
What is specifically done to 1221 stations with max and min records, for 365 days a year for over 100 years – that works out as much as 89,133,000 individual records – obviously this is done by some kind of algorithm which must have a large number of tunable assumptions – how exactly is that done – take the high side on assumption 5 and the high side on assumption 11 and, viola, +0.3C.
Well the warming shrill in australia is cooling. It is starting to cool off here both in temps and support for warming. Fear is behind this. The extrmists are afraid of warming, afraid if we don’t tax, they will die of heat. They are afraid of storms. The true fear they need is the consequences of when the wheels fall off the hoax. There is no authority to adjust temps upwards and then have the nerve to claim after adjustment, their theory is suppported.
Joe Romm is trying to make some man connected to Ken Lay from enron and now ignores It was enron that started the trading of SO2 futures, sold their wind business to GE and indocrtrinated Hames Hensen. Hensen was in the tank with enron. In the 80’s and with the clintons. If Joe romm claimed to work for the clintons, he should know how they kissed his bosses.
timetochooseagain (14:26:18) :
but it is not appropriate to claim that you are getting the “raw” data by subtracting NOAA’s USHCN from GISS GLOBAL Data.
Perhaps you should re-read (maybe me too) the post, but that’s not what he is doing as far as I can tell. He is taking the difference between NOAA’s raw and adjusted data sets (which is in Figure 3), then discussing the similarity to the NASA GISS global temperature anomaly (which is in Figure 4). I.e., he’s making the claim that the US adjustment as supplied by NOAA is remarkably similar to the global anomaly record as supplied by NASA GISS and pondering: coinicidence, or no?
Mark
layne Blanchard (14:22:43) : Actually, the Sea Surface Temperatures were measured back then rather sparsely with various methods like buckets, engine intake, etc. The “adjustment” procedures going on in the SST’s are troubling because they are hardly ever brought up vut from what I can tell extremely dubious. Search CA for “buckets” or:
http://www.climateaudit.org/?cat=67
One major problem is poor sampling, especially early in the record, since very few measurements were apparently being made.
However, When data are missing there is an “infilling” procedure (at least for surface stations) which is related to some of the “correction algorerythms” used to “adjust” for biases in the network. Basically they take the info from “nearby” (something like 1200 km away, I think) and plug the gaps. Probably something similar was done for SST’s.
Sandy (13:42:55) : No. Not that the agree anyway:
http://www.climatesci.org/publications/pdf/R-345.pdf
It is common for fossil power stations to use large lakes for cooling water which will in turn warm the lake water. Utilities sometimes must add cooling towers to reduce the warming effect, but all the same, you can’t use lake water for temperature trends if there are power stations co-located nearby.
don’t tarp me bro (14:37:06) : Worse than that-he wrote books praising how great Enron was for their “stance” on AGW etc.
This article show the utter significance of Anthony’s surface station project.
Do I have to say more?
Hi there.
Regarding Figure 5: trend line fit of temperature versus year. I found that when making trend line fits to data in Excel chart, that Excel assumes, by default, that the error is completely on the x-axis variable . So be careful if plotting temperature versus time as obviously the error is on the y-axis temperature measurement.
I am sure the people making Figure 5 are already aware of this.
Kind regards
Tim
Bill D (14:05:23) : “no one has claimed that Urban heat effects can influence the temperature of large lakes.”
I wonder why not? Without any data I so claim. Not long ago I commented about irrigators taking water out of streams, rivers, lakes, and ground water. Spread that water out over dark-soil fields and the return flow back to the streams will be warmer. Do I need proof of that?
In urban areas take water and spray it on pavement, lawns, golf greens, wash things (cars, windows, patios +++), use it for food processing, spraying for dust control, impound it (fish ponds, swimming pools, bird baths, road depressions +++), and a few dozen other uses. All of these uses will allow the water to warm before it returns to the streams and lakes.
“. . . such as Lake Washington (Seattle) . . .”
What about all the wine barrels that get cleaned with water/steam/ozone there in Woodinville and the landscaping and pavement and highways there about. What are the local water sources (snow melt off the Cascades?), temperature of the in-going water and that sent out to Lake. WA?
Your post suggests that you or colleagues are in a position to investigate this issue. What say you?
Mark T (14:41:53) : Re-reading it looks like you may be right…unfortunately the from text it is difficult to tell what was done. The GISS graph is probably confusing a lot of people…As an editorial choice I would have left it out.
This together with surfacestations.org exposes the truth as in Figure 5.
They adjusted the numbers to fit the answer. They cheated us. I hope any NOAA or NCDC scientists are embarrassed enough to speak up now. Dr Hansen please explain how when you use the raw data there is now warming?
Everyone thought Exxon had the formula to convert coal to oil well the real secret was the so called scientists fixed the data to get the answer their supporter politicians and activists needed.
It’s kind of like the doctors around Michael Jackson. They kept pumping him with drugs until he finally gave out only we’re next so to speak.
Professor John Brignell wrote along very similar lines in his “Numberwatch” blog in July 2007, see http://www.numberwatch.co.uk/manmade.htm and came to exactly the same conclusion.
Question: who are the gate-keepers?
I reluctant to except a global conspiracy, but in my theory the sixties-seventies hippies just grownup, got into powerful position (media, management etc)
and now they can fulfill they dream to enforce a hippie ideology, social engineering, nanny state etc.
Just a thought…
Off subject, but have you all reviewed some of the online blogs having to do with the censored EPA Report issue ? OMG – it’s a full on personal attack of Alan Carlin ! It’s as if every natural cycle denier in the world is going after his credentials and aspects of the report (which no doubt were due to the short prep time).
I’ve felt for awhile that have been approaching a “tipping” point in perception of AGW, but this Climate Bill vote and some of the collateral effects of its backers to rush it into law are bringing the debate to a head. Personally I think people have reached the “enough is enough” point with what going on in Washington, but when a bill this significant is pushed on them – they have a right to understand the scientific assumptions behind it are wrong.
The United Nations (therefore the IPCC) polls very negatively with Americans. If they really understood the connection between the IPCC, AGW ideology agenda, and long term affects that will result from this bill – it would not pass the Senate.
How do we connect the dots for the public ?
Excellent work. Too bad we couldn’t get this to more congressidiots before this past week’s vote.
How does Figure 5 tie in to the causes and effects of the “dustbowl” drought of the 1930’s? Surely it would be a marker of extremes like “ice skating on the Thames”?
To complement Mike Hammer’s results, here’s a link to my March 2, 2009 post about SST anomalies of U.S. Coastal Waters.
http://bobtisdale.blogspot.com/2009/03/sst-anomalies-of-us-coastal-waters.html
The Northern Gulf of Mexico and the Western North Pacific datasets showed higher SST anomalies in the 1930s and 1940s than during the more recent period of elevated SST anomalies. For the Eastern North Pacific, the peak in the late 1990s was slightly higher than the peaks in the 1940s and 1950s.
All of this is looking more and more Enron-esque with each passing day. How much longer can they cook the books before it all comes crashing down?
Michael Hammer’s paper confuses two different things. The USHCN adjustments were applied to CONUS (lower 48) data, and relate to local US measurement procedures. They were not applied to global data, and in no way “explain” the global warming trend.
REPLY: There’s a similar set of adjustments applied to the Global Historical Climatological Network (GHCN). USHCN is better documented than GHCN, and this make an easier target for analysis. Both data sets are adjusted. – Anthony
I find the notion of adjusting rural temperatures up to eliminate UHI … uhm “interesting”. While that does certainly reduce the UHI difference between urban and rural locations, it isn’t any reflection of reality.
To then use that adjusted data as “proof” of general warming is not dishonest, it seems to be to be quite despicable.
With Copenhagen coming up and the type of legislations Europe and the US are preparing, I am very concerned that the records -temperature etc…- will be re-written, that there will be a tentation to re-write history according to the Gorespel of AGW and CO2 so all traces of unbiased data will be erased. Already they claim that thermometers reading before the 1950s should be corrected so the late XX century warming keeps growing… Revisionism? If anyone was attempting the same manipulation of WW2 history, they’d be thrown in jail and have legal troubles… Not so here since governments are directing their scientists and pouring money into the official revisionism.
Anthony,
Of course GHCN results are adjusted, but to what effect? Anyway, Michael is talking about Hadcrut3, of which land GHCN is a minor component. And yes, SST are adjusted too, but in quite different ways. This post in no way establishes that global warming measurements correspond to any adjustment that has been made to them.
REPLY: Feel free to go on thinking that. – Anthony
Regarding the upcoming Copenhagen meeting, permit an old retired guy to ask what (if any ) preparations people are making in the event that it meets the expectations of the AQW crowd, or conversely, collapses and makes all the anti-crowd happy. Any legal, political, or other challenges in work? Or are the losers just going to pout and throw hissy fits?
http://www.cbsnews.com/stories/2008/12/31/60minutes/main4694713.shtml
Totally unrelated to this thread, but this scares the pants off me. The applications are….. unthinkable. (No pun intended)
It has always baffled me why the urban heat island affected surface record should have a positive adjustment attached to it while the 1930s should be negative.
At least scientifically it has baffled me.
While James Hansen is in charge of it, I’m not surprised by anything.
@Jack Green (15:35:49) :
“Everyone thought Exxon had the formula to convert coal to oil well the real secret was the so called scientists fixed the data to get the answer their supporter politicians and activists needed.”
Where do you get your information?
Exxon and others do have technology to convert coal to gas, and from there to liquid fuels, however we generally refer to this as Coal-to-Liquids or CTL. It is not a secret technology, and the “answer” you refer to was not fixed. The result in the early 1980s was that crude oil must be $38 to $40 per barrel for the CTL process to break even. Knowing this, OPEC set a world price for benchmark crude oil at $36 per barrel. Not much of a secret.
Knowing this will shed some light on why OPEC strives to maintain crude oil price under $80 per barrel.
This proves anthropogenic global warming (i.e man-made adjusting of the data).
On a more serious note though I think the 64 thousand dollar question is whether the adjustments are legitimate.
From the Wong-Fielding meeting on Global Warming:
“For the last two decades the alarmist scientists have been safe in the knowledge that the
valid criticisms of their theories and models are just a little bit more complex than the
politicians and most of the public are willing to hear. On the other hand, the alarmists
have lots of time and media space to get across the complexities of their message. But
finally, after the usual warming cycle apparently ran its course by 2002, the public and
politicians are noticing that temperatures are not rising as the alarmists said they
would—and the public and politicians understand temperatures!”
crosspatch (16:01:05) :
They do have control of the datasets, and the opportunity.
Which leaves only motive.
I can only tell you that in times past (30 yrs ago) you could look up much older records than you can today. I can also attest to seeing reported new record highs where the older ones have been ‘wiped clean’ by dumping anything before 1950.
There is monkeymotion aplenty to be found.
Considering that a majority of stations are producing errors > 2C, and assuming that when the first versions (Stevenson screens, unwired, and whitewashed), the instrumental error was probably very small, due to the paint and much less urban warming effect, should the raw data show an actual increase nevertheless?
If the data shows no increase, wouldn’t that be indicative of an actual overall global cooling compared to, say, an era when urban sprawling did not affect most stations?
PaulH wrote: “All of this is looking more and more Enron-esque with each passing day. How much longer can they cook the books before it all comes crashing down?”
Benford’s Law on the distribution of leading digits is sometimes used to catch those who “cook” financial records. However with data such as temperature that has a restricted range, can Benford’s Law be adjusted to take this into account?
See “Applications and Limitations” section in:
http://en.wikipedia.org/wiki/Benford's_law
There is also a distribution on the second leading digits which may not be as sensitive to data with restricted ranges.
(See “Generalization to digits beyond the first” section in the above.)
Anthony: Thanks for providing the link to the older GISTEMP data archived at John Daly’s website. I used it for a trend comparison of GISTEMP Contiguous U.S. Surface Temperature Anomalies, before and after the post-1999 adjustments.
http://bobtisdale.blogspot.com/2009/06/contiguous-us-gistemp-linear-trends.html
Before the post-1999 GISS adjustments to the Contiguous U.S. GISTEMP data, the linear trend for the period of 1880 to 1999 was 0.035 deg C/decade. After the adjustments, the linear trend rose to 0.044 deg C/decade.
It’s obvious that by showing these numbers you are in danger of affecting the new rollerball government takover. They know where you live.
When I first saw this at Jennifer’s blog the my first thought was that it was statistically improbable that all adjustments would be positive. As I look at figure 2 more closely I can see the plots for individual adjustments don’t square with information about surface station history.
Firstly the red plot for thermometer type looks to be the right shape, but is upside down. There should be a negative adjustment for enclosure paint changes around 1979, followed by an gradual adjustment later in the decade for MMTS introduction. Anthony might be able to answer as to the likely direction of MMTS adjustment.
Secondly the pale blue plot for data infilling looks statistically improbable. The infilling appears wholly positive. Surely this plot should appear as noise centered on the X axis?
The yellow plot for station siting excluding UHI appears to be upside down. The general increase in man made structures around surface station could be expected to create a warm bias in station microclimate. An indication of increased siting issues due to the introduction of MMTS on short cables also appears to be missing in this plot.
The purple plot for UHI appears to be the correct orientation, but should show a marked increase in magnitude around the 1990s for rural station dropout.
As to the TOB adjustments, well I don’t know how or why these are made. I would be fascinated to read why time of observation errors are not random in sign or magnitude. Why is it considered that time of observation issues have introduced a negative bias needing such a large correction that is increasing over time?
A strange blog entry as it simply quotes stuff from the referenced page with few invalid statements added.
Bill Illis (14:32:11) quotes a recent paper 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
and this tatement is just plain WRONG
Since the total corrections for the US look so similar to the claimed temperature anomaly
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!!!!
So what it comes down to is do we believe a blog or the American Meteorological Society.
Tricky!
REPLY: “A strange blog entry as it simply quotes stuff from the referenced page with few invalid statements added.” I’ve added nothing, your statement is in error. The post is the same here as it appears on Marohasy’s blog here:
http://jennifermarohasy.com/blog/2009/06/how-the-us-temperature-record-is-adjusted/
– Anthony
When you look at the GISS treatment of Australian temperature data, you find that most Australian data have been homogenised at home more than once before being sent to various repositories that end up at GISS. Now, GISS does some similar adjustments a second time, on top of the former. It’s not so simple though, because GISS does not seem to know what has been done to the Australian data before they get it, or after, or which version they are starting with. I’m half way through a long study of this effect, so these comments are preliminary but I suspect inarguable. I have asked Micheal Hammer if he wants to collaborate because he’s working globally on data of mixed origin and I’m working in detail on subsets with discrete data from as many sources as I can get. Even within Australia there are different versions at some stations. These can be unannounced until you study their differences.
If you need a simple example, see
Station Name Lat Lon ID Pop. Years
(*) Echuca 36.1 S 144.8 E 501948610000 rural area 1881 – 1992
(*) Echuca 36.1 S 144.8 E 501948610001 rural area 1881 – 1981
at http://data.giss.nasa.gov/cgi-bin/gistemp/findstation.py?datatype=gistemp&data_set=0&name=Echuca
Remember that 100 years ago people were using the data for farming and transport and planning bridge heights for floods and a few tenths of a degree was neither here nor there. It’s a bit optimistic to reconstruct the Earth, the Universe and Everything from them today.
Geoff Sherrington (19:15:04) :
Why, 42 of course.
bill (19:00:33) : REPLY: “A strange blog entry as it simply quotes stuff from the referenced page with few invalid statements added.” I’ve added nothing, your statement is in error. The post is the same here as it appears on Marohasy’s blog here:
– Anthony
My statement was meant to reference the original blog, sorry.
By the way I particulary like the scientific use of the fig 5 curve fit, Why on earth would anyone try to fit the curve to that data?
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.
Of interest:
Talking Points related to: Is the U.S. Temperature Record Reliable?
http://www.ncdc.noaa.gov/oa/about/response-v2.pdf
EXAMINATION OF POTENTIAL BIASES IN AIR TEMPERATURE CAUSED BY POOR STATION LOCATIONS
http://ams.allenpress.com/archive/1520-0477/87/8/pdf/i1520-0477-87-8-1073.pdf
REPLY: Old news Bill, we’ve already covered that here
http://wattsupwiththat.com/2009/06/24/ncdc-writes-ghost-talking-points-rebuttal-to-surfacestations-project/
Peterson has no scruples. When I was at NCDC to talk about the weather station survey project, he demanded to be put on the agenda so he could lecture me about his views entirely unrelated to the topic. Even his coworkers were irritated because it wasn’t relevant to the discussion we were having. – Anthony
For the “magic 1221” USHCN1 surface stations, 1900 – 2006 (equally weighted):
Raw: +0.14C
With TOBS adjustment: +0.31C
With FILNET: +0.59C
Therefore, on a station-by-station basis, adjustments are more than quadruple raw and almost double with TOBS.
(USHCN2 puts it at +0.72C, if I recall correctly.)
Bill,
I too feel that the curve fitting in figure 5 is of little value. I also feel that the comparison of USHCN adjustment plots to global data in figure 4 is an unwarranted extrapolation. But the plots in figures 1 to 3 are of great concern.
Figure 2 is of particular interest. Many of the issues pertaining to the reasons for surface station data adjustments have been discussed on this site. I would not be the only reader to notice that historical changes to surface stations that I am aware of are not reflected in the individual adjustments in figure 2. The TOB adjustment is particularly disturbing. This clearly requires more investigation.
Focusing on minor issues such as Michael Hammer’s curve fitting in figure 5 will not make the issues writ large in figures 1 to 3 go away.
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
Last ime I dealt with deg F was 30years ago when I lived at home. One assumes a science blog would use SI units by now ! :o)
REPLY: “One assumes a science blog would use SI units by now !”
OK that’s just disingenuous, An apology is in order from you, Bill
1) NOAA standardizes on F, where the rest of the world and science uses C or K. NOAA’s entire temperature database is measured in F, recorded in F. It is the unit of the United States and for this reason they must conform to that.
2) I didn’t write the post and I’m not in the business of modifying the work of others to conform to SI, that includes bloggers and NOAA
3) Don’t like F ? Neither do I, complain to NOAA, but don’t throw snark at me because you don’t understand why F is used in studying the US temperature record.
If the surface data is no one say fraudulent, do we assume that the satellite data was ‘calibrated’ against adjusted surface data thus polluting all global temperature datasets?
Dr, Christy says not, and I believe he is trustworthy.
But satellite data measures lower troposphere, not surface, and if there is a warming trend, lower troposphere is said to warm 1.2 to 1.4 (depending on latitude) times more rapidly than surface.
Dr Hansen please explain how when you use the raw data there is now warming?
Dr. Hansen does not use raw data. GISS procedure is as follows:
1.) Take fully adjusted USCHN data.
2.) Apply an “unadjustment” algorithm.
3.) Apply a “readjustment” algorithm.
It is my understanding that the time of day observation adjustment (TOBS) is non controversial. I think Anthony Watts confirmed this once. What does the data look like if the TOBS adjustment is left in.
+0.314C for the average station. (Raw is +0.141C.) This is the straight average for all 1221 USHCN stations.
There remains some question as to how accurate this adjustment is. NOAA does not use the actual time of observation data from the B-91 forms, but uses an algorithm, instead. Therefore is no way of knowing how accurate this adjustment is.
I’d like to repeat your summary of “correction” trends:
Konrad (18:44:50) :
When I first saw this at Jennifer’s blog the my first thought was that it was statistically improbable that all adjustments would be positive. As I look at figure 2 more closely I can see the plots for individual adjustments don’t square with information about surface station history.
Firstly the red plot for thermometer type looks to be the right shape, but is upside down. There should be a negative adjustment for enclosure paint changes around 1979, followed by an gradual adjustment later in the decade for MMTS introduction. Anthony might be able to answer as to the likely direction of MMTS adjustment.
Secondly the pale blue plot for data infilling looks statistically improbable. The infilling appears wholly positive. Surely this plot should appear as noise centered on the X axis?
The yellow plot for station siting excluding UHI appears to be upside down. The general increase in man made structures around surface station could be expected to create a warm bias in station microclimate. An indication of increased siting issues due to the introduction of MMTS on short cables also appears to be missing in this plot.
The purple plot for UHI appears to be the correct orientation, but should show a marked increase in magnitude around the 1990s for rural station dropout.
As to the TOB adjustments, well I don’t know how or why these are made. I would be fascinated to read why time of observation errors are not random in sign or magnitude. Why is it considered that time of observation issues have introduced a negative bias needing such a large correction that is increasing over time?
—
TOB: What specifically changed in time, when was it changed, and why does the TOB bias continue to ramp up? Are they measuring at ever-earlier minutes before noon every year?
Which stations are UHI corrected? What is the regional UHI effect: A down town station should go “up” more than a mid-urban, and and mid-urban station should go more than a mid-suburban, and UHI not at all for a rural station until 1980-1990. How many stations in an area are UHI corrected? Why are downtown areas routinely +10 degrees F HOTTER than suburban temperatures, IF the UHI effect is only 1/2 of one degree C?
“Siting” corrections should NOT be constantly increasing. Unless “all” stations are continuously getting more and more interferences around them? At a uniform rate nationally?
evanmjones (21:27:29) :
Station moves: Ok, a few (100 or 200 maybe out of their claimed 1200) have moved. But they do not continuously “move” and drive a continuously changing “station movement” correction.
Unless the “station movement” plus “TOB” changes are intended to mask/enhance/confuse the gradually increasing UHI change:
And UHI IS the ONLY “continuously ad gradually increasing over time” temperature bias – and the ONLY one that is NOT being corrected in recent records.
As to the TOB adjustments, well I don’t know how or why these are made. I would be fascinated to read why time of observation errors are not random in sign or magnitude. Why is it considered that time of observation issues have introduced a negative bias needing such a large correction that is increasing over time?
The short story is that if measurements are taken in the morning (closer to Tmin), TOBS bias will make them cooler. If taken in the afternoon (Closer to Tmax), the TOBS bias will be warmer.
This is true, and if you set up an example it becomes obvious. (The question is that of degree.)
There has been a shift from afternoon readings to morning readings.
I’m probably coming late to the game here, but how can the time of day observation adjustment (TOBS) continue to rise over the recent decades? This would seem to suggest that the temperature measurement has been made toward cooler and cooler times of day over the years (for example, earlier in the morning, or later in the evening). Is this really what the TOBS adjustment is doing? Or is TOBS addressing something different than “time of day” altogether, notwithstanding its name? Perhaps TOBS is attempting to capture some assumed relative difference vis-a-vis the older temperature data, rather than adjusting the new data per se?
followed by an gradual adjustment later in the decade for MMTS introduction. Anthony might be able to answer as to the likely direction of MMTS adjustment.
It’s slightly positive. About +0.02C since the introduction of MMTS.
I’m probably coming late to the game here, but how can the time of day observation adjustment (TOBS) continue to rise over the recent decades? This would seem to suggest that the temperature measurement has been made toward cooler and cooler times of day over the years (for example, earlier in the morning, or later in the evening).
That’s what they claim. (A shift from afternoon to morning.)
OK, I see Robert A Cook and evanmjones posted while I was still reading the comments and preparing my question.
Follow-up question for evanmjones:
So if I understand you correctly, my third suggestion was actually closest, namely: “Perhaps TOBS is attempting to capture some assumed relative difference vis-a-vis the older temperature data, rather than adjusting the new data per se?”
Specifically, as more stations slowly switch from afternoon readings to morning readings over the years the overall TOBS is increased, not so much to adjust the morning readings themselves, but to instead provide a number that allegedly matches what the new readings would have been had they been taken in the afternoon like the old data.
Station moves: Ok, a few (100 or 200 maybe out of their claimed 1200) have moved. But they do not continuously “move” and drive a continuously changing “station movement” correction.
There are many, many local station moves. Only a very few stations have not been moved. Most have been moved several times. Every time a company closes, a plant moves, or a private volunteer passes on (or loses interest), there is a station move. In most cases when the CRS was converted to MMTS, there was a local move. They move continually. To wit, Lampassas, TX . . .
MMS records of station moves are incomplete, and often inaccurate.
And UHI IS the ONLY “continuously ad gradually increasing over time” temperature bias – and the ONLY one that is NOT being corrected in recent records.
Sometimes the mountain comes to Mohammed. It doesn’t have to be urban, suburban, or exurban creep (though it may be). It can take the form of a new driveway or paving a gravel or dirt road. Or a wing added to the house. Or a new patio. Over time it adds up. No records of any of this exists.
but to instead provide a number that allegedly matches what the new readings would have been had they been taken in the afternoon like the old data.
That is my understanding. At least that is what the NOAA graph shows.
David S “On a more serious note though I think the 64 thousand dollar question is whether the adjustments are legitimate.”
Absolutely! You can find details at CDIAC or at NOAA.
There are three USHCN changes that had substantial effect. Allowance for UHI change gave apparent cooling; TOBS and SHAP increased the apparent heating. TOBS is time of observation bias. It is to do with the choice of reading time during the day – chiefly for min-max observations. This wasn’t standardised for US stations, and changed over time. SHAP concerns the actual movement of individual stations, or other significant changes. Clearly both situations do require adjustment. The basis for them is set out in papers by Karl and others, written in 1986 and 1987. These rules have been followed since. The adjustments are based on lots of public information, and have not been substantially challenged over that time.
There were two others – MMTS, which was a one-off recalibration when they changed min-max thermometers to thermistors in about 1990 (less than 0.1F increase) and FILNET, which interpolates for missing data. Again, FILNET had fairly small effect, and since 1910 has been fairly neutral.
Note that all these adjustments relate to specific issues with US stations. Those issues will not be the same for other land stations, and of course are quite different for sea temperatures. There is no basis for suggesting, as this post does, that they are responsible for global temperature rises.
REPLY: Nick stop saying that, you are putting words in Mr. Hammers and my mouth. You are the only person jumping to this conclusion, and it is wrong.
1- post title – USHCN (not global, not GHCN)
2- conclusion “…artefact arising from the “corrections” applied to the experimental data, at least in the US,” Note US caveat.
3- The GISS global figure is for shape comparison only.
4- The same people that managed USHCN, with all the adjustment issues raised here, also manage GHCN, so it is possible there may be similar issues, but we aren’t looking at GHCN, only USHCN. GHCN will get a look I’m sure.
Until then keep your conclusions, like the title, in the USA. – Anthony
evanmjones (21:39:12) :
“It’s slightly positive. About +0.025C since the introduction of MMTS.”
Does that mean MMTS sensors read hotter or colder than older thermometers? are they reading .025 hotter needing ajustment down or reading colder needing the .05F to .075F upward ajustment shown?
Also with TOB, I thought both Tmax and Tmin were recorded each day. Is there a link to information how both the older and newer surface station equipment works, and standard procedures for readings?
“Totally unrelated to this thread, but this scares the pants off me. The applications are….. unthinkable.”
You cant take three from two,
Two is less than three,
So you look at the four in the tens place.
Now thats really four tens,
So you make it three tens,
Regroup, and you change a ten to ten ones,
And you add them to the two and get twelve,
And you take away three, thats nine.
Is that clear?
Don’t worry until they start applying adjustments to your thoughts . . . “I know what you were REALLY thinking!” (Of course, for those who are married this is old hat.)
Sorry, I got distracted by the light blue infilling plot. I meant .03F upward ajustment for MMTS…
A little closer to 0.04F. (I readjust my estimate to 0.02C.)
Does that mean MMTS sensors read hotter or colder than older thermometers?
A little bit cooler. But that is only if placement is identical to the CRS it replaced. What we have found, however, is that in the large majority of cases, placement of the MMTS is inferior. Anthony believes that this is due to problems related to trenching the cable, and I agree.
John F. Hultquist (15:15:09) :
Bill D (14:05:23) : “no one has claimed that Urban heat effects can influence the temperature of large lakes.”
I wonder why not? Without any data I so claim. Not long ago I commented about irrigators taking water out of streams, rivers, lakes, and ground water. Spread that water out over dark-soil fields and the return flow back to the streams will be warmer. Do I need proof of that?
In urban areas take water and spray it on pavement, lawns, golf greens, wash things (cars, windows, patios +++), use it for food processing, spraying for dust control, impound it (fish ponds, swimming pools, bird baths, road depressions +++), and a few dozen other uses. All of these uses will allow the water to warm before it returns to the streams and lakes.
John:
I’m talking about big deep lakes, including lakes where water renewal from the water shed takes decades. Two of the biggest lakes with strong records of warming in the surface waters (top 100 meters or so) are Lakes Tahoe and Lake Baikal. I know that there was discussion on this blog about how geothermal influences might affect Baikal. However, warming of the deep waters is < 0.1 oC for that lake and nearly all of the warming is in the upper 100 m. If you know anything about LaKe Tahoe (mostly California) you would not expect water shed activities to influence the temperature. In fact, heat budgets for the lakes in question generally show that 99+% of the temperature change of the surface waters is caused by in lake warming. Cold water inflows during winter is the main cause of temperature changes and mixing in the deep waters of lake Baikal, accounting for the small changes (< 0.1oC) and the presence of O2 at great depth.
I think that the articles in press are very good summaries, but you may be able to access articles on Lakes Washington, Tahoe, Zurich and Baikal throughGoogle scholar without fees. The data for Lake Washington goes back about 50 years and shows peaks in temperature associated with ENSO.
This is an off topic question, but I know of know good places to ask besides here. Why is 30 years the important trend? If CO2 and temps over a century are the numbers we are using to extrapolate a trend from, why not compare 100 years of temps?
Also with TOB, I thought both Tmax and Tmin were recorded each day. Is there a link to information how both the older and newer surface station equipment works, and standard procedures for readings?
For the USHCN, it’s all min-max, regardless of system. Therefore it all comes down to time of observation. If TOBS occurs right around Tmax or Tmin, big problems will occur: A spike will “carry over” to the next day, effectively “counting it twice” and wiping out the next day’s “true” Tmax or min.
If you keep measurement time well separated from the hottest and coldest point during the day, there should be no problem.
(It also shouldn’t matter much if it’s morning or afternoon, so long as it is at the midway point between typical Tmax or min periods. But NOAA claims there is a tendency for a lag, so mornings may have a bit of a cool bias and afternoons a warm bias.)
Evan wrote: “If TOBS occurs right around Tmax or Tmin, big problems will occur: A spike will “carry over” to the next day, effectively “counting it twice” and wiping out the next day’s “true” Tmax or min.”
And I think here is exactly where the logic error occurs and why TOBS adds to the magnitude of the record.
Evan, for example you just assumed that the previous day’s Tmax would “swamp” the next day’s Tmax. That is ONLY true if the previous days Tmax is greater than the next. If the following day’s Tmax is higher, then no problem.
Same holds true in reverse for Tmin.
The TOBS methodology is a logical mess. – Anthony
evan that is the new math
of course we do it in our head as 42-3 is 39
oh well.
42= 30+12
12-3=9 9+30=39
got it
To be more precise 30 years refers to the trend we are ‘currently’ in, and 100 years is the trend we predict.
Well, as the master says, It all depends whether you are over 35 or went to a private school or under 35 or went to a public school.
liberal or conservative school ? that is my take, i am 50 and got it in grammar school here.
Why is 30 years the important trend?
Well, it starts right around when the PDO and SO flipped and the warming trend started. It also coincides with the era of satellite measurement. And it is a long enough period of time to make the data statistically significant. (Though it seems to me the ending of the Younger Dryas did in three years what they normally do in thousands and that ought to be statistically significant enough to be going along with.)
I think if the temps fall 5F in the next two years some heads will roll….. lol
maybe they can add 5 to all the station across the board!!!!!!!
never mind the snow in the keys or Bahamas!!!!
That is ONLY true if the previous days Tmax is greater than the next. If the following day’s Tmax is higher, then no problem.
Certainly. (That’s what I meant by a “spike”. I should have made it clearer.)
The TOBS methodology is a logical mess. – Anthony
Gosh, yes. Did NOAA ever release its algorithm for that like sure ’nuff scientists? (Or are we still talking typical NCDC alchemy?)
Anthony,
The co2 bill is in the Senate , we need your work published ASAP, WE ARE OUT OF TIME.
oh well stuff happens!
REPLY: Peer reviewed journals don’t usually run on the authors schedule on anybody else’s – Anthony
[REPLY- Unless of course it’s The IPCC and the Hockey Stick redux! ~ Evan]
liberal or conservative school ? that is my take, i am 50 and got it in grammar school here.
The main difference these days is that in the former case you don’t need to get the right answer to receive full marks.
(“I would have given him a B, but I couldn’t afford the lawsuit.”)
I think if the temps fall 5F in the next two years some heads will roll…..
Nah, they have that covered with The Day After.
evan it’s called promotion !
REPLY: Peer reviewed journals don’t usually run on the authors schedule on anybody else’s – Anthony
Correct and that is how it will be held out of the playing field until there objective has been made.
The mathematics of spin.
I did not get published until I wrote for a conservative paper, they ( the libs.) said my writing was a mess, or unintelligent, or whatever to put it down!
Good luck in getting it through the masher. play by there rules to get it in.
So the red plot should show a slight drop (-.05?) for the introduction of latex paint followed by a smooth increase to +.02 not +.04 during the introduction of MMTS.
The yellow siting plot should probably be inverted, and show a recent further downward adjustment for the MMTS cable issue.
The light blue data infilling plot looks statistically improbable, and should probably be recentred on the x axis.
The purple UHI plot should be included in calculations, and amended to show a serious downward adjustment during the period of rural station dropout.
As to the black TOB plot, I am having trouble conceiving of how an algorithm that does not directly use times of observation for individual stations can generate a meaningful adjustment.
As far as I can see, any significant warming trend shown in the adjusted USHCN record is an artifact of said adjustments. Having said that, I still feel that trying to apply corrections to data from stations rated below CRN-2 is an exercise in scientific futility. It might be useful in supporting political agendas…
So 30 years is arbitrary? I was thinking that thirty years is a very short time in the sense of climate, and 100 is also short, but then at least we are looking beyond the life cycle of a person.
And why add the recent year and drop the old year on the thirty year trend? Why not just add the new year? Just to entertain your math conversation we can refer to it as the 30+X where X equals Year to n. Eh, I don’t think it’ll catch on.
I have done some further reading on Tmax/Tmin readings using the electronic recorder for MMTS sensors. As far as I can see there is the possibility of transposing data from one day to another ie: using one days Tmax or Tmin twice. However this would only occur once if a station changed from morning to afternoon readings. Even if a station operator made observations at almost random times each day, the monthly average should not show a warming or cooling bias. I can see no scientific basis for TOB adjustments for the electronic MMTS system. I will need to read more about the previous measurement system, but I think it is fair to call shenanigans on TOB adjustment after 1985.
bill (20:48:18) REPLY: “One assumes a science blog would use SI units by now !”
OK that’s just disingenuous, An apology is in order from you, Bill
1) NOAA standardizes on F, where the rest of the world and science uses C or K. NOAA’s entire temperature database is measured in F, recorded in F. It is the unit of the United States and for this reason they must conform to that.
It was a mild quip (no snark intentded) hence my attempt at a smiley.
The CDIAC site talks of both C and F in the same document!
The data referenced at http://cdiac.ornl.gov/ftp/ushcn_monthly/hcn_doe_max_data.Z
seems to be in F
http://www7.ncdc.noaa.gov/CDO/mapproduct is in degF
ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/v2/ is in deg C (*10)
I’m sure you are aware of this (an amusing read in comments on occasion!) http://www1.ncdc.noaa.gov/pub/data/uscrn/ushcnsitesurveys/
for example “Please leave the thermograph. Sherry loves it.” “Existing HCN site is marginal. Elderly host does not want new equipment.”
Konrad (20:45:35) : the comparison of USHCN adjustment plots to global data in figure 4 is an unwarranted extrapolation. But the plots in figures 1 to 3 are of great concern.
…
Focusing on minor issues such as Michael Hammer’s curve fitting in figure 5 will not make the issues writ large in figures 1 to 3 go away
If you look at the overlay I did and multiply the height of the adjustment by 5/9 I think you will agree that the adjustment makes no noticable difference to the temperature plot (global) which shows a significant increase.
http://img198.imageshack.us/my.php?image=uhcnadjust.jpg
To try and respond to some of the comments made on this site. Some of you have commented that the trend lines plottd in graph 5 are not warranted. I included them for two reasons. The linear one because AGW advocates are claiming an underlying increasing temperature over the 20th century. If that were the case a least squares linear trend line should show it. Why try second order? Because episodes such as the medieval warm period cause a rise in temperature followed by a fall and the little ice age the reverse. A parabolic or 2nd order trend line would show that up. In both cases the trend line is an extremely poor fit to the data which means they signify very little. If you look at the original I do clearly state that no underlying trend can be determined from the plotted trend lines. Their value (and reason for inclusion) is because they show precisely that.
With regard to one graph in C and the other in F, the problem is that these are not my graphs they are reproduced from cited websites. To make the scales conform I would have had to replot them in which case i would have left myself open to claims I modified the data. As Antony rightly pointed out I was drawing a comparison of shape (not of absolute magnitude) and I was not doing so as a conclusion in its own right but as a trigger to have a look at what the raw data really looked like.
I have seen several comments on both this site and Jennifer’s site implying that I am objecting to a specific correction (usually TOBS) and that claiming the correction is justified invalidates my argument. My concern is more basic. We have here a very comprehensive data record collected over many years. The raw data shows no trend. The data is adjusted and after adjusting shows a trend. Inference, the trend has been introduced by the adjustments made. To use this created trend to justify an hypothesis is very risky and doubly so if the people carrying out the adjustments are supporters of the original hypothesis. Please note that I do not want to imply by this statement that the people involved are deliberately fudging data. I believe them to be honest reputable scientists. However experiments showing how easily unintentional bias can creep into adjusted data are legion. Thats why double blind experiments were devised.
Some things that raise alarm bells for me. Having looked at UHI effects for a medium sized city in some detail it is very clear that the UHI effect is both large and very non linear, increasing in rate in more recent times. For Melbourne the data suggests 1.5C in the last 40 years or 3.75C per century. To use a linear correction does not seem justified. To use a magnitude of 0.06C per century implies only 1 in around 60 sites is affected by UHI (assuming the rate computed for Melbourne is typical). I doubt if one could find 59 rural sites with comprehensive temperature data for each urban site in the USA.
The upwards correction for sites moved out of the city I have already referred to.
A correction for time of day may or may not be justified but why is it continuously increasing at an accelerating rate. Are measurement time continuously changing and at an accelerating rate? And why always to make the temperature warmer?
Why are all the corrections one way – amplifying the supposed AGW signature? Nature is rarely liek that. Why is the UHI correction now deleted?
What about the degrading siting that Antony so elequently demonstrated. Such degradation is likely to increase warming arund the affetced measuring sites. Why is this ignored?
Are there other corrections that should be applied yet have not been?
I can only say again that to create a trend by adjusting data and then using that trend to justify an hypothesis is a very dangerous approach.
A questions for everyone reading this. If this scenario was in relation to testing of a new drug, do you think the FDA would be happy to accept the findings? If not, why should we now. The stakes for our society are far greater than would be the case with an individual drug.
A large part of the correction comes from TOBS. One might expect random variations but it’s difficult to see how it could lead to a strong trend over fifty years. It has been stated on this thread that there was indeed a consistent migration from morning to afternoon readings. For this to occur over half a century does stretch credulity a bit bit I suppose it is possible. So my question is this: can anyone give a link to the actual data and scientific research that this claim is based on?
Of course, as I understand it this discussion is specific to the US temperature record. Is it likely that the same situation (i.e. most of the warming derived from corrections) also applies to the global temperature record?
Finally, is there any other science where vast conclusions are drawn from data that is mostly based on corrections?
Chris
evanmjones (21:35:41) :
The short story is that if measurements are taken in the morning (closer to Tmin), TOBS bias will make them cooler. If taken in the afternoon (Closer to Tmax), the TOBS bias will be warmer.
Evan, I took these measurements for 5 years (1981-1986) while stationed at the USDA-ARS Central Great Plains Reasearch Station in Akron, CO., so I have some experience. I’ve not mentioned this before. The question I have is; if you take a measurement once a day in the morning as is done, the thermometers will record the low of the night before measurement, and the high of the previous day. The previous days high may be recorded “incorrectly datewise” relative to the low recorded presumably after midnight, since the day date changes at midnight (obviously). However, answer this: Why should the temp be adjusted at all? You are still getting the max temp for a 24-hr period, just perhaps not in conjunction with the corresponding 24-hr period low. With my experience I see no valid reason for a TOBS adjustment to alter temperature at all. The TOBS adjustment should presumably only adjust the correlation between max and min for a particular 24 hr period, and not the absolute temp at all. To make it clearer (maybe), when I recorded the max and min temp within the stevenson screen, I recorded an absolute min/max. per day, the same as one who recorded at noon, but either of my min/max may have been attributable to a different 24-hr period. However, the average over the month would be exactly the same.
There’s an unmistakable anthropogenic effect upon climate data.
Well, it TOBS occurs at the right time (well away from Tmax or Tmin, I doubt there should be any adjustment. The times should have been standardized nationally, but were not, presumably because the NWS was trying to predict weather, not record century-long trends to a hundredth of a degree.
(Also, the TOBS problem may not have been realized early on.)
Nick Stokes (22:01:37) :
“On a more serious note though I think the 64 thousand dollar question is whether the adjustments are legitimate.”
Absolutely! You can find details at CDIAC or at NOAA.
There are three USHCN changes that had substantial effect. Allowance for UHI change gave apparent cooling; TOBS and SHAP increased the apparent heating. TOBS is time of observation bias. It is to do with the choice of reading time during the day – chiefly for min-max observations. This wasn’t standardised for US stations, and changed over time.
….
Absolutely not!
Focus on just one: TOBS. You claim that the data needs changing “It is to do with the choice of reading time during the day – chiefly for min-max observations. This wasn’t standardised for US stations, and changed over time.”
We see above that TOBS “corruption” over the century accounts for almost all of the supposed AGW increase that will now cost us 1.3 trillion dollars.
So, prove it.
Show exactly how with the numbers for the entire US stations, not with some abstract unsubstantiated claim, are adjusted. Calculate exactly why the TOBS correction increased continuously ONLY through the last half of the century century – when reading times changes both ahead and behind noon, reading times DID NOT change continuously over the nation but in ones and two’s at isolated stations, changing both ahead and behind, and once changed, did not change back. A single correction for time at a single station is NOT a continuous increase for ALL stations across the WHOLE country that continuously INCREASES with time.
What? Is EVERYBODY now reading a max/min thermometer ever earlier in the morning every day, only that the previous day’s max and min both changed because the thermometer was read ever earlier every day over the whole period?
2) UHI is now NOT corrected. Why? It is the ONLY effect that HAS increased linearly with time.
3) UHI “correction” was NEGATIVE for ALL data from 1900 through 1970. Why? That UHI correction was NEGATIVE (the flip chart at the top of the threads show ONLY the the early temperature was corrected down, the later temperatures uniformly were “corrected” up. Show us why.
Conclusion: Several writers above claim that there is no corruption, no deliberate falsification.
I would change that: It is up to the AGW community to prove beyond a shadow of a doubt that the AGW community has NOT falsely corrupted the data it is using to claim a 1.3 trillion dollar tax increase.
We KNOW absolutely that many previous AGW-favorable studies have been falisified data, falsified numerical analysis, falsified conclusions from the analyzed data, and have been (deliberately) written to exaggerate certain pre-ordained conclusions. Your (the AGW community of extremists) track record shows that the burden of proof of accuracy lies on your side.
Look at the chart of raw vs adjusted temps again: click
Note that the highs and lows all match the raw data [the red squares] prior to about the early 1960’s. But some time after that, the official record starts getting “adjusted.”
But notice that it is only the high temps that are adjusted higher. The low temps are not adjusted lower, they match the raw data.
The net result is to show more warming than has occurred.
OK, a few technical issues on the TOBS adjustment. The usually cited authority for this is the paper of Karl et al 1986, and some other papers at about that time, referred to in the CDIAC and NOAA docs I cited above. Again I note that these protocols have been current for over twenty years. They are based on much publicly available information, and haven’t been discredited in that time. If you want to start discrediting them now, you’ll have to study the basis for them rather carefully.
So Chris Wright, here’s your link.
And Konrad, why TOBS adjustments after 1985? The reason is that they adjust to be correct for a specific reading time, for consistency over the record. I think it is midnight. There’s no “correct” time; the best you can get is consistency. If the current reading time is not the long term standard, then there will be ongoing adjustments. This illustrates the illusoriness of the fuss about the magnitude of the adjustments. If they had chosen something close to current practice as the standard, then the current adjustment would be much less. But it wouldn’t make any real difference.
And Tim Clark, how does TOBS cause multiple counting? Evan has been explaining it well. Let me try a specific example. Suppose the instrument is read and reset at 9am each day. Suppose Monday is a very cold morning, bottoming at 6am. Then that bottom is the minimum recorded for Sunday. And the 9am temp (also very cold) is the minimum recorded for Monday, replacing whatever low was reached on Tuesday morning. That cold Monday morning is recorded twice. Maximum’s won’t be split in the same way, so it is a cold bias. If instead the reading time had been 5pm, the opposite process would lead to a warm bias. If the reading time changes over the years, there is a trend. And there’s no point in speculating about whether the reading times have changed. It’s recorded fact; Karl and others have looked at the data, done their calcs, and these have stood for over twenty years.
So Robert Cook, the things you want shown are in Karl’s papers and elsewhere. There’s no claim that EVERYONE changed their times etc – just enough to make the difference. It isn’t true that UHI is now not corrected. It’s just that the correction is made within the general framework of consistency adjustment. This is just nomenclature; the methodology was always similar. UHI correction was always negative and decreasing.
And Michael Hammer – ditto about UHI “deletion”. It isn’t true that the corrections are “all one way”. There are two, TOBS and SHAP, that have lead to significant increases. On the CDIAC graph that you cited, one, UHI, has lead to decreases. FILNET gave a rise from about 1900 to 1910, and has been fairly neutral since. And MMTS was a small one-off recalibration for the introduction of thermistors in the early 90’s. As with all these changes, what do you suggest? That the data should seriously be used uncalibrated?
Robert A Cook PE (10:49:02) :
Also, I’d expect there to be some regional variations. E.g. Mostly sunny vs. mostly cloudy. Frequent/Occasional frontal passages. Sea breeze/Inland. Big shifts in hours of daylight through the seasons (Key West and Hawaii vs northern tier and Alaska).
I’d expect the biggest impact to be on days with inconveniently timed frontal passages. Every year we have a few days where the high temperature for the day is at midnight and a cold front comes through between then and noon with snow and firece Canadien winds and what limited sun we have, even if the clouds break, has no chance to warm us up to better the temperature at 0000.
ohioholic (23:26:01) :
I’m not confident in the following, but it might be right.
The 30 year window has been used in the past going back at least to days when computers were programed by cards, and probably back when computers were often college students on summer break. As such, it made sense to compile typeset by Liotype machine a 30 year reference.
Since then, people learned about the PDO and AMO, the satellite record is just about 30 years, and even a PC ready for dumping in China can produce “last 30 years” data with publication-ready output, either on paper or .pdf file.
One problem with the “last 30 years” or “last 60 years” to try to get a whole PDO cycle” is that research papers will all be referring to different “last 30 years” and it will be as hard to compare current data with the average, just as we need to know the monthly vintage when referring to GISSTEMP with all those backfilled data.
No wonder the models had to make up something that isn’t happening, water vapor feedback; they were hindcast to events that didn’t happen. I’m sorry I’m laughing myself sick. Sick at my uncapped and rising energy bills. I’m going to have to trade my soul to pay the bill. Funny, real funny.
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Nick Stokes (14:03:22)
Thanks for your link to the Karl et al paper. It will take me some time to get through all of it, but I have already found some areas I want to look into further. I hate to say this but some of the work is model based and the paper’s conclusions mention climate change. Red flag to a bull etc.
With regard to the other USHCN adjustments shown in figure 2, I still see concerns that have not been answered.
A. While the red plot showing adjustments for instrumentation changes seems correct in showing a positive adjustment for MMTS introduction, it should also show a negative adjustment of similar magnitude representing the introduction of latex paint for Stevenson screens around 1979.
B. The yellow plot for siting issues should be inverted, and include a sudden negative adjustment for the short cable issue at the introduction of MMTS.
C. The light blue plot for infilling correction seems to be indicating that data infilling (creation) has a constant negative bias that needs to be corrected for. If this plot is not random in sign and centered around the x axis, questions need to be asked about infilling methods.
D. The purple UHI adjustment should show a significant negative adjustment at the time of rural station drop out in the 1990s.
I have to agree with those such as Evan who say that without reference to time of observation data for individual stations, a generalized TOB algorithm has little efficacy. If TO is recorded as well as Tmax and Tmin, why is this data not being utilized? I am beginning to suspect that physical experimentation for TOB such as Anthony did with shelter coatings may be needed.
I do not see that Michael Hammer is in any way out of line in questioning these adjustments. Much of the history known about USHCN stations is not evidenced in the adjustment plots.
In Australia, many if not most weather stations changed from daily reading/resetting to half hourly. This was in the period approx 1989-1996. The half hour recording apparatus was largely replaced by one-minute recording for the high quality network about year 2000.
An instrument that gives a more-or-less continuous trace over 24 hours is not affected by TOBS. Simple daily inspection will show Tmax and Tmin, whenever they occur. Therefore, the last 20 years of data sent from Australia to GISS has no reason to have TOBS applied. I am currently studying how often it is.
Also, given the small number of days each year that a TOBS effect operated on mercury thermometers, coupled with the fact that most obs were then averged to get Tav from Tmax+Tmin/2, the error carried forward was likely to be halved. Putting these together and running scenarios, the likelihood of the TOBS error being of the size shown for the USA is probably incorrect for Tav. We shall never know until a count of the days when TOBS effect operated eavh year is revealed. If it happened on 5% of the days, the annual error is then 1/20 of the measurement error, roughly. There appears to be no justification whatsoever for its continuation once automatic, multiple daily recording was introduced.
I know that this repeats the sentiments of others who have posted above and my own old posts on CA. I have yet to see an explanation for the shape or magnitude of the USA corrction curve shown above.
The final point is that there would be more than one station observer in the USA who knew of the TOBS effect when recording daily readings and who had the nous to read the device again to get a correct reading for each day, or at least note the second reading in the metadata. Until the metadata examination results refute this possibility, one has to accept it as plausible. In those days people seemed to be more concerned with doing their reporting accurately and noting exceptions, because it was “their” data and their reputations relied on it.
OT perhaps, but still Australia centric. This is what the New South Wales govn’t is doing in terms of “informing the public”…
http://savepower.nsw.gov.au/
Little black balloons of CO2 floating up into the sky….
Although I am all in favour of saving power, consuming less (Originally from the UK which has always had high energy costs and I have lived in an area of New Zealand that has/had the highest unit price for electricity – it also happens to be one of the poorest regions there too) I learnt not to waste stuff.
fwiw, the land grant universities in your state may very well have a parallel non adjusted dataset that could be compared to the GISS datasets. When I’ve done this with the MO sites for the University of MO, I can’t find any trend at all.
“Little black balloons of CO2 floating up into the sky….”
Let’s see, the atomic mass of N2 is what? And O2 is what? So balloons filled with CO2, with it’s greater mass, is “floating up into the sky”. They must be using one of the IPCC’s models to get that result.
Barring rare events, such as a frontal passage that may invert the expected time of high (mid-afternoon) and low (sunrise) temperatures, there’s no way that reading at nearly the same time of day a Tmax/Tmin instrument is going to lead to great confusion. At, say, 9am one gets yesterday’s high and today’s low as a rule, rather than the 9am teperature per se. The whole idea that switching, say, to 10:30am would lead to substantial bias in monthly averages–one which evolves over time in the aggregate, to boot–needs to be critically re-examined.
Bill D (22:43:09) : large lakes
I appreciate the additional information and clarification.
I have been following the warming debate with interest especially Anthony’s survey of weather stations. Prof. Vincent Courtillot thinks that we have very different weather patterns in different parts of the world, however even though I am a skeptic on AGW, in my short life time of 62 years I am pretty sure we have seen either warming or significant changes in weather patterns here in the UK. 40 years ago wide spread snow in winter was common here even in the south of England and Wales but we have hardly seen snow for the last 20 years. So has there been a distinct warming that perhaps is now entering a cooling phase or is it just there are different patterns in different parts of the world, even in different parts of the USA?
Hi, wattsupwiththat.com – da best. Keep it going!
Have a nice day
@ Nick Stokes (14:03:22)
Thanks for the link to the Karl 1986 paper. But this paper describes a method for estimating TOBS and does not contain a study of actual TOBS trends. However, it does contain a table that shows a continuous trend from AM to PM measurements from 1931 to 1984 (percentage of AM readings goes from 14 to 42). Unfortunately they do not give the source of this data, which is surprising in a scientific paper. Do you have a link to actual scientific studies of the TOBS trends? Many thanks.
Chris
It is interesting the the derived “raw” data in figure 5 show a peak in 1930 which corresponds to the “dust bowl”. The dust bowl was caused by drought and bad farming practices. Maybe it was quite hot too.
Chris Wright,
The most comprehensive review of world adjustment practices is this 1998 review paper. Unfortunately it is behind a paywall, and also does not have the detailed information on actual TOBS trends that you are seeking. It does describe the GHCN adjustments, which are limited to homogeneity, and do not include TOBS. For TOBS specifically, the 1986 paper does seem to be the most quoted reference.
Here is a paper by Karl et al on the MMTS adjustment.
“jtom (21:47:51) :
“Little black balloons of CO2 floating up into the sky….”
Let’s see, the atomic mass of N2 is what? And O2 is what? So balloons filled with CO2, with it’s greater mass, is “floating up into the sky”. They must be using one of the IPCC’s models to get that result.”
Well, as N2 makes up 78% of the atmosphere, I used that in an e-mail to the person at the “contact us” link at that site. So I e-mail the contact stating that N2 has an atomic weight of about 15, whereas CO2 is 44. Pointed out the fact that CO2 cannot “float up into the sky as if it is lighter than air and in a black balloon”, political spin and misinformation. Pointed out the fact that mercury (In the ecobulbs) is infinitely more poisonous than CO2 (Reference to Japan and people eating fish contaminated with mercury).
No response.
Can anybody get me a copy of :
Mitchell, J.M., Effect of changing observation time on mean temperature, Bull. Am. Meteorol. Soc., 39, 83-89, 1958.
I can’t retrieve it from BAMS. The search function will not bring it up. It appears to be the first cited paper.
For Chris Wright (again)
I think this 2003 review of TOBS is what you are looking for. Unfortunately, it is also behind a (fairly small) paywall.
Has anyone attempted to extrapolate the adjustments into the future? Just by eyeballing the charts it looks like the adjustments could becomes several degrees by 2100. Makes one wonder about the methods being used.
Nick Stokes (05:50:59) :
For Chris Wright (again)
I think this 2003 review of TOBS is what you are looking for. Unfortunately, it is also behind a (fairly small) paywall.
For your money, this might be a better investment.
Pielke, Roger A., Christopher A. Davey, Dev Niyogi, Souleymane Fall, Jesse Steinweg-Woods, Ken Hubbard, Xiaomao Lin, Ming Cai, Young-Kwon Lim, and Hong Li (2007), Unresolved issues with the assessment of multidecadal global land surface temperature trends, J Geophys Res, 112, D24S08.[CrossRef]
Richard M (07:27:20) :
Has anyone attempted to extrapolate the adjustments into the future? Just by eyeballing the charts it looks like the adjustments could becomes several degrees by 2100.
—
Richard, Richard…. Haven’t been keeping up with the news?
MIT did just that study a few weeks ago, and came up with a whirling prediction circular pieplate (er, template) that ALL corrected UHI thermometers will read +9 degrees by the year 2010.
Come on. Ya gotta keep up better!
@ Nick Stokes (05:50:59)
Nick, thanks for your efforts. If there are any papers available that are free that would be great but, failing that, I wonder if you could briefly describe the basic explanation for this trend. You would certainly expect random changes, depending on who happens to be running the station, but there would have to be some systematic change that led to a consistent trend over fifty years. I would be intrigued to know what it was.
Many thanks,
Chris
Chris W,
Here is another recent paper with lots more detail (free). And here’s what they say about the history of TOB:
I would also love to know the justification for TOB trends. My current CAD modeling can find no justification for TOB adjustment outside of half day step changes once off for change in TO. I get the same Tav Monthly for TO at 0700, 1700 and 2400 reading and reset for MMTS using typical summer diurnal profiles and winter profiles. WUWT? If I introduce extreme (Tmax, Tmin randomly overlaping TO) red noise to my pseudo diurnal profiles, TOB is random in sign. Even though I have now read the Karl et al 1985 paper, I am not convinced of the need for TOB adjustments. If TOB adjustments are preformed without reference to the TO recorded for individual stations, I suspect these adjustments belong in the wicker filling cabnet. If these adjustment are preformed over the top of data infilling add a can of lighter fluid and a struck match…