The saga about measurement of temperature, in the United States, at least, is growing in reach and noise, and there are now dozens of websites with thousands of posts about it. One of the main temperature datasets, that of the Goddard Institute for Space Science (GISS), a part of NASA, is now in the news for what critics call ‘dancing data’. The GISS dataset is the one that the orthodox prefer to use, because it shows consistently warmer trends than all the others.
One Canadian sceptic, Walter Dnes, has been downloading GISS data every month for several years, and has downloaded lots more earlier data from the wonderfully named ‘Wayback Machine‘, which archives what appears on the web at the time it was placed there. Mr Dnes has a particular interest in temperature data, and the work he has done, not just for this post, is impressive indeed.
Mr Dnes then published his findings on WUWT. It turns out that the data do dance about, so that trend lines change their size and their sign for no obvious reason. For example, ‘In 7 years (December 2005 to December 2012), the rate of temperature rise for 1910-2005 has been adjusted up from +0.6 to +0.8 degree per century, an increase of approximately 30%.’ The essay contains lots of worrying statistics of this kind. We are in the land of ‘adjustments’ and ‘homogenisation’ again. And to make the point again, these are old data, past data, and they seem to change over time, again and again. In this particular case the data don’t all become cooler in the past and warmer in the present, the worry in my last post on this matter, but that is not the point. They just keep changing.
All this worries me, as a data-cruncher from way back, because anyone who works with data needs to be confident that the data are valid and reliable. When past data change you wonder what has gone on, and how solid your conclusions really are. Conspiracy theorists will remind you of Winston Smith, in Orwell’s 1984, whose job in the Ministry of Truth was to rewrite historical documents as the party line changed. It’s a neat analogy, but I distrust the rush to conspiracies.
The Commenters on Mr Dnes’s paper included someone who pointed out that the people at GISS don’t adjust data — that is done for the Global Historical Climatology Network (GHCN) by other people at NOAA/NCDC (sorry for all these abbreviations). Further discussion suggested to me that what we see in these data is a mixture of real temperature data, estimations and modelling. I doubt that it is now possible to disentangle the ‘data’, and doubt also that they can mean much.
The discussions led to a slanging match between the defenders of thermometers (the land-based and sea-surface temperature measurements) and those who prefer the measurements gained by satellites. The thermometer-lovers pointed out that the satellites don’t measure temperature at all, but ‘radiance’. I thought I knew about that, but decided to check. Dr Roy Spencer, who has been associated with the UAH temperature dataset from the beginning, describes it as follows:
Since 1979, NOAA satellites have been carrying instruments which measure the natural microwave thermal emissions from oxygen in the atmosphere. The intensity of the signals these microwave radiometers measure at different microwave frequencies is directly proportional to the temperature of different, deep layers of the atmosphere… [and the outcome is] global temperature datasets … that represent the piecing together of the temperature data from a total of fourteen instruments flying on different satellites over the years.
Wikipedia adds The satellite series is not fully homogeneous — it is constructed from a series of satellites with similar but not identical instrumentation. The sensors deteriorate over time, and corrections are necessary for satellite drift and orbital decay. Particularly large differences between reconstructed temperature series occur at the few times when there is little temporal overlap between successive satellites, making intercalibration difficult.
Does that inspire confidence? I prefer the satellite datasets (RSS and UAH) because of their near-global coverage, but I accept that that the datasets contain error. Fourteen instruments on several different satellites over 35 years? It would be extraordinary if there were not error.
Of course, the thermometers don’t measure temperature either. There are a great many types of thermometer, and each of them uses a change in something else to infer a change in temperature. All of them have problems. None of them is perfect. All temperature measurements have error. It seems to me that, for the most part, the likely error could be at least as large as the the change in temperature over time.
The longer these angry arguments drag on the more I am persuaded by some wise words of Tony Brown, a British climate historian who is interested in human records of climate experience over the past thousand years (and longer):
Sometimes those producing important data really need to use the words ‘ very approximately’ and ‘roughly’ and ‘there are numerous caveats’ or even ‘we don’t really know.’
It is absurd that a global policy is being decided by our governments on the basis that they think we know to a considerable degree of accuracy the global temperature of land and ocean over the last 150 years.
Amen.
Yes, of all the measurements made, satellite are the only ones that are truly global and uniformly calibrated. The satellites are in polar orbits, so they can cover the whole globe with time. And yes, they do have to be corrected for various factors, including orbital drift, non-uniform instrumentation and so on.
Ground station measurements are not global–they don’t cover the oceans, for starters, which fill 72% of the Earth’s surface. Neither do they cover the Sahara desert, Amazon and Congo jungles, Siberia, Tibet, and the icy deserts of Antarctica and the Arctic. Furthermore, as it’s been pointed elsewhere, almost all ground stations are compromised in various ways, be it with respect to siting, or because their situation has changed over the years due to urban encroachment, or because their thermometers are not properly calibrated, etc. It is therefore quite telling when *unadjusted* data returned by the US Reference Network of 114 exemplary stations shows… cooling by 0.4 deg C over the past 10 years. Surprising?
http://www.forbes.com/sites/jamestaylor/2014/06/25/government-data-show-u-s-in-decade-long-cooling/
Yes, “global warming” is a hoax, rooted in pseudo-science of climate models, shoddy measurements, and plain, old-fashioned cheating, hiding behind unscrupulous manipulation and alteration of data. Yet, even IPCC and the US National Climate Assessment reports are *forced* to admit that no trends in weather patterns, in extreme weather events can be seen over the past century. It is easier to “adjust” temperature by another 0.2 deg C, than to falsify hurricane, tornado and drought statistics.
The public, the politicians, industry captains ought to know they are being lied to. Kudos to those who tell them.
Gus this line of argument has been done to death. For example the whole motivation for Professor’s Richard Moller’s re-analysis of the relationship between temperature and CO2 was that he did not want the data to be “cleaned”. So he re-analysed 14 million data points from 44,000 different sources.
Your argument that some how the majority of these temperature data could have been doctored to materially change the AGW result is pathetic!
If I remember correctly, Moller’s paper was rejected.
The point is, there is *no* “AGW result.” There is no proof whatsoever of, first, there being anything wrong with the weather–both IPCC and US National Climate Assessment admit this–and, second, of humans having any impact on it, outside of urban areas. Furthermore, there is no real global data for the time before 1979, that is, when satellite measurements commenced, and there is no evidence at all that the slight temperature rise from the time, when it was particularly cold–as everybody well remembers–to the end of the 20th century was in any way abnormal and not driven by natural processes. The end of this temperature rise, as soon as solar activity, excessive in the last two decades of the 20th century, abated, is further proof that the “AGW result” is completely wrong.
In 2011, Santer et al, argued in their Journal of Geographical Research paper, doi:10.1029/2011JD016263, that “temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature.” Guess what: it’s been 17 years now, more than 17 years in fact, that no only has there been no global warming. Instead the world has cooled, the cooling rate being -0.36C/century.
It is ridiculous to imply that 14 million temperature records from all sources could be doctor sufficiently to give a false result.
David,
Aren’t you taking about Richard Muller (not Moller) and the BEST project? It is certainly the case that he has gone back to the original data. The problem there is that the SST measurements are not worth anything, while the most complete land set is that of the USA, but even that is compromised. We are looking at an alleged rise in temperature of about 0.8 degrees C over a century, but the real error in all these data must be around the same size, if not greater. And as Gus points out, the new reference set in the USA actually shows cooling for the last decade.
It is certainly possible that the planet has warmed, and there are other non-tthermometer reasons for thinking so, but these data, on which so much weight is placed, are awfully rubbery.
Don
Gus quoted forbes.com
“Yes, “global warming” is a hoax, rooted in pseudo-science of climate models, shoddy measurements, and plain, old-fashioned cheating, hiding behind unscrupulous manipulation and alteration of data.”
Is that your view that AGW is based on “old fashion cheating” ?
“Gus quoted forbes.com”
So? Is the comment in Forbes factually incorrect? You can inspect the data referred to yourself. It’s public, and made available by NOAA.
“Is that your view that AGW is based on “old fashion cheating”?”
Yes. In view of the vast bulk of scientific literature published on the subject in peer reviewed journals, in view of data, in view of observations, there is no “AGW.” None that you can point your finger at and say “people did this.”
Climate fluctuates naturally in response to variations in solar activity, variations in the earth’s orbital parameters, variations in ocean currents and ocean multidecadal oscillations. It is naturally affected by the always varying cloud cover, volcanic activity, seasonal changes, boreal forests, tropical jungles, oceanic plankton, etc. The natural factors are all-powerful, have been swaying the climate for millions of years and will continue to do so. There is nothing about the climate and climate variation today that is in any way unusual in view of past records. The lack of any global warming in more than 17 years now, in spite of atmospheric CO2 concentration rising considerably in the same time is proof, experimental and observational, that CO2, at present day concentrations, is not a climate factor.
Yep.
How is the Forbes comment factually incorrect? Is the NOAA data wrong?
Which reference are you referring to? Gus does not appear to read the references he cites, much less display any ability to interpret their results.
Not ridiculous at all, if the records come from US standard weather stations, nearly all of which are compromised producing results of very poor quality, usually too high, on account of their poor placement, e.g., at airports, near buildings, and because of urban encroachment. This has been *documented* in Fall et al, Journal of Geophysical Research 2011, doi:10.1029/2010JD015146. Of the 82.5% of all US weather stations surveyed (1007 of 1221 stations) 64.4% were shown to yield errors greater than 2C, 21.5% produced errors greater than 1C and 6.2% returned errors greater than… 5C!!!
Quoting from the paper:
“Comparison of observed temperatures with NARR shows that the most poorly sited stations are warmer compared to NARR than are other stations, and a major portion of this bias is associated with the siting classification rather than the geographical distribution of stations. According to the best?sited stations, the diurnal temperature range in the lower 48 states has no century?scale trend.”
What does the situation look like elsewhere? Well, this paper by Ozdemir et al, in Theoretical and Applied Climatology 2012, doi:10.1007/s00704-011-0515-8, finds warming in cities of Anatolia, but none in the country. And this paper by Heinrich et al in Climate Dynamics 2013, doi:10.1007/s00382-013-1702-3, looks at tree rings and finds no warming at all in the Eastern Mediterranean.
Gus
You really are clueless! The data are time series.
So? All data is numbers. In this case, the data is numbers (temperature read out in deg C) versus time. If the readouts are loaded with *systematic* error, plus a random one, all your readouts will suffer from the same *systematic* error. See “Systematic Error” in Wikipedia, if you lack scientific training.
“All your readouts will suffer from the same *systematic* error.
Well only if you were a statistical neophyte. It would be relatively easy to control for these so these called systematic errors. Off the top of my head one could add in the add in a variable distance-from-a-capital-city and if this variable was statistically significant such that the coefficient on CO2 was no longer statisticaly significant you would have a case.
But you don’t!
“one could add [] in a variable distance-from-a-capital-city and if this variable was statistically significant such that the coefficient on CO2 was no longer statisticaly significant you would have a case.”
And this is exactly what happens. See doi:10.1029/2010JD015146 and doi:10.1007/s00704-011-0515-8
Gus
I suggest you read the article you cite before you ask me to read. I have copied the full abstract and capitalised the bits you need to concentrate on!
The authors report that while choice of weather station has an affect on diurnal temperature range it has NO effect on average temperature.
AGW is a hypothesis about average temperature! This article does not support your claims!
doi:10.1029/2010JD015146
Analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends
The recently concluded Surface Stations Project surveyed 82.5% of the U.S. Historical Climatology Network
(USHCN) stations and provided a classification based on exposure conditions of each surveyed station, using a rating system employed by the National Oceanic and
Atmospheric Administration to develop the U.S. Climate Reference Network.
The unique opportunity offered by this completed survey permits an examination of the relationship between USHCN station siting characteristics and temperature trends at
national and regional scales and on differences between USHCN temperatures and North American Regional
Reanalysis (NARR) temperatures. This initial study examines temperature differences among different levels of siting quality without controlling for other factors such
as instrument type. Temperature trend estimates vary according to site classification, with poor siting leading to an overestimate of minimum temperature trends and an
underestimate of maximum temperature trends, resulting in particular in a substantial difference in estimates of the diurnal temperature range trends. The opposite?signed differences of maximum and minimum temperature trends are similar in magnitude, SO THAT THE OVERALL MEAN TEMPERATURE TRENDS ARE NEARLY IDENTICLE ACROSS SITE CLASSIFICATIONS. Homogeneity adjustments tend to reduce trend differences, but statistically significant differences remain for all but AVERAGE temperature trends. Comparison of observed
temperatures with NARR shows that the most poorly sited stations are warmer compared to NARR than are other stations, and a major portion of this bias is associated
with the siting classification rather than the geographical distribution of stations.
According to the best?sited stations, the diurnal temperature range in the lower 48 states has no century?scale
trend.
I’d be inclined to emphasize these sentences: “Comparison of observed temperatures with NARR shows that the most poorly sited stations are warmer compared to NARR than are other stations, and a major portion of this bias is associated
with the siting classification rather than the geographical distribution of stations.”
Also, I’d like to draw your attention to the last sentence: “According to the best?sited stations, the diurnal temperature range in the lower 48 states has no century?scale
trend.”
This is an important observation, because, you see, the AGW theory claims that the night temperatures should rise, on account of CO2 “greenhouse effect,” while the daytime temperatures should be less affected.
See my comment above. Stop digging, you will end up in Australia 🙂
Do you mean, you didn’t know about the diurnal cycle temperature range fingerprint of “greenhouse effect?”
As a matter of fact you experience it yourself, since, if I remember correctly, you live in San Francisco. The diurnal temperature range at sea-side locations is markedly smaller than the diurnal temperature range in a desert. This is because the presence of water vapor, the most powerful of all “greenhouse” agents, moderates temperature changes. So, in a sea-side location, temperature rises slowly in the morning, does not climb very high, and drops slowly overnight. In a desert, temperature rise is very fast, very high temperature is reached during the day, higher than at sea, then at night temperature drops rapidly, oftentimes to below freezing, way lower than at sea. The diurnal temperature range in a desert may reach between +50C and -10C.
So, if there was an accumulating greenhouse effect at work, we would expect to see progressively smaller diurnal range at weather stations. The fact that at the best weather stations, that is the ones that return most accurate results and are least tainted with the proximity of urban structures, we do not see such an effect at all over the past 100 years, implies that we do not see a “greenhouse effect” fingerprint in the observed climate drift. It must, therefore, be caused by something else.
Now, here is the latest on the urban heat island effect and how profound it really is–nobody argues with this, but this is not related to CO2. See “Strong contributions of local background climate to urban heat islands” by Zhang et al (it’s a Yale group), Nature 2014, doi:10.1038/nature13462. In some cities of America, this effect is responsible for additional 3 deg C and is worst in wet climate. And the effect is not confined to cities. It turns out that cities can affect temperatures for *thousands* of miles. See “Energy consumption and the unexplained winter warming over northern Asia and North America” by Zhang et al (the lead author is from Scripps, UCSD) in Nature Climate Change 2013, doi:10.1038/nclimate1803.
A study in China, carried out by Wu and Yang, doi:10.1007/s11434-012-5627-8, 2013, found that urbanization in eastern China has a profound effect on climate there: not just in the cities, but throughout the whole region, in particular, their results show that the urbanization can induce a remarkable summer warming in the whole Yangtzy River Delta city cluster region and a winter warming in Beijing-Tianjin-Hebei cluster region.
So if you have weather stations located in such regions, what is it that they actually measure?
The diurnal cycle temperature range? Yes its called night and day.
Keep digging . 🙂
The diurnal cycle temperature range is the span between the lowest and the highest temperature in 24 hours. This span is smaller in places with abundant water vapor in air and larger in dry areas. If the warming that had occurred since the end of the Little Ice Age, most of it before 1960, was caused by human emissions of CO2 and the “greenhouse effect” supposedly triggered by it, this would be reflected in the span getting gradually lower all around the world. The best sighted weather stations in the US don’t show any such trend over the past 100 years.
Here is more from the same paper, Fall et al, Summary and Discussion:
“The comparison of time series of annual temperature records from good and poor exposure sites shows that differences do exist between temperatures and trends calculated from USHCNv2 stations with different exposure characteristics. […] The magnitudes of the significant trend differences exceeded 0.1°C/decade for the period 1979–2008 and, for minimum temperatures, 0.7°C per century for the period 1895–2009.”
… Wow! Isn’t 0.7C all there is to “global warming” to begin with? The net global temperature rise since the end of the Little Ice Age?
“The CRN 5 stations are on *average* warmer than the CRN 1&2 stations compared to interpolated NARR temperatures by about 0.7°C. However, when the differing geographical distribution of stations is taken into account, the difference attributable to siting characteristics alone is about 0.3°C.”
This is still huge difference, because 0.3C is all the global warming that has occurred in the last two decades of the 20th century. It is important to remember, in this context that most of the late 19th and 20th century warming, about 0.4C, has occurred prior to 1960, when CO2 could not possibly have been a factor.
Gus,
If you find yourself in a hole, stop digging. 🙂
Hi David,
I’m having problems trying to understand a couple of your points.
1. If I understand the paper correctly, siting has a strong effect on temperature trends with poorly sited stations giving too warm minimums and too cool maximums irrespective of their geographical location. The average of two bad estimates of similar magnitude tend to cancel out and (as re your CAPS) the average trends for siting and geography are similar. The best-sited stations (re the last line of the abstract at the bottom of your post) show ‘no century-scale trend’.
And in their summary (p. 13) “Overall, this study demonstrates that station exposure does impact USHCNv2 temperatures. The temperatures themselves are warmest compared to independent analyses at the stations with the worst siting characteristics. Temperature trend estimates vary according to site classification, with poor siting leading to an overestimate of minimum temperature trends and an underestimate of maximum temperature trends, resulting in particular in a substantial difference in estimates of the diurnal temperature range trends.”
I’m not seeing any support for an AGW signal here, just a demonstration of systematic bias in temperature data collection at most sites with the best sites showing no trend. The relatively new (2005) U.S. Climate Reference Network that was set up to control for these problems shows a 0.4 C cooling trend for the lower 48 states. So, these results seem to support Gus’ claims of no AGW signal in the US temperature data.
2. Above you say “AGW is a hypothesis about average temperature!” Well, not really, and not about averages of well-sited and poorly sited stations. AGW is a hypothesis that as anthropogenic CO2 increases, the average temperature of the globe will increase more than expected from the physical characteristics of the molecule because of positive feedbacks in the climate system. Corollaries include a stronger increase at the poles than in the tropics, more effect at night than during the day, atmospheric hot spots, etc. There is no support for AGW in this paper that I can see.
3. Above you say “Off the top of my head one could add in the add in a variable distance-from-a-capital-city and if this variable was statistically significant such that the coefficient on CO2 was no longer statisticaly significant you would have a case.” I can’t understand this point at all. What ‘statistically significant coefficient on CO2 ‘ is there?
Cheers,
Dave
DavidW
“I’m not seeing any support for an AGW signal here.”
Exactly!!!!!!! The paper does not address AGW, at all. Gus asked me to read it because he felt it proved that positioning of temperature gauges was some sort of smoking gun that disproved AGW.
If Gus was in the habit of reading more than he writes he would have noticed that authors state that positioning of temperature gauges had NO effect on MEAN temperatures, which is obviously a central tenet of the the AGW hypothesis.
Yes really. 🙂
You can only compensate for systematic errors if you know the cause. Now suppose the wind patterns change when you move a station? Or when buildings are added around the thermometer? I recall a fellow who instrumented his back yard. The numbers were all over the place and there was no easy way to correlate one thermometer (electronic) to another. The micro-environment is not smooth. It is chaotic.
And all the records don’t come from US standard weather stations!
Weather stations all around the world are located near towns or in the cities, most often at airports, right next to concrete and steel structures. Where they were located in the country, in China, for example, the cities grew and closed on them, and, in many cases, about which the Chinese wrote themselves, they moved the stations closer to the cities to facilitate servicing and maintenance. The problem of weather stations is endemic. It’s the same everywhere. They are useless for reading any “climate change” out of them.
This is why satellite measurements are so important and why we can safely ignore most land-based data, perhaps with the notable exception of weather stations specially constructed, like the 114 ones in the US, to serve as reference for all the others.
Weather stations all around the world are located near towns or in the cities.
Well that is rubbish.! There are weather stations on Macquarie Island , Broom and Cloncurry.
“There are weather stations on Macquarie Island , Broom and Cloncurry.”
Yes, but few and near buildings. Read the paper I referred you to about the US stations: it discusses the issues and the bias that accompanies the measurements.
[…] that they don’t believe the RSS data, and prefer that from GISS, I could ask had they read my last post on that subject. They probably wouldn’t […]
Don
Now here is a link to a paper by Muller on this very topic of temperature measurement and it capacity to bias estimates of AGW. Again I have capitalised one sentence to drive home the point. They report that
“A survey organized by A. Watts has thrown doubt on the usefulness of historic thermometer data in analyzing the record of global warming. That survey found that 70% of the USHCN temperature stations had potential temperature biases from 2°C to 5°C, large compared to the estimated global warming (1956 to 2005) of 0.64 ± 0.13°C. In the current paper we study this issue with two approaches. The first is a simple histogram study of temperature trends in groupings of stations based on Watt’s survey of station quality. This approach suffers from uneven sampling of the United States; its main value is in illustrating aspects of the data that are counter-intuitive and surprising. The second approach is more statistically rigorous, and consists of a more detailed temperature reconstruction performed using the Berkeley Earth analysis method indicates that the difference in temperature change rate between Poor (quality groups 4, 5) and OK (quality groups 1, 2, 3) stations is not statistically significant at the 95% confidence level. THE ABSENCE OF A STATISTICALLY SIGNIFICAT DIFFERENCE INDICATES THAT THESE NETWORKS OF STATIONS CAN RELIABLY DISCERN TEMPERATURE TRENDS EVEN WHEN INDIVIDUAL STATIONS HAVE NOMINALLY POOR QUALITY RANKINGS. This result suggests that the estimates of systematic uncertainty were overly “conservative” and that changes in temperature can be deduced even with poorly rated sites.”
http://www.scitechnol.com/2327-4581/2327-4581-1-107.php
But what I really want to draw your attention to is not the lead author by the 7th author, who is none other than your favourite go-to sceptic Judith Curry!
So at least in this paper Muller, Curry and others DO NOT accept that measurement error is an issue. I certainly put more store in their analysis than the climate babble that Gus produces and I suggest you do the same.
No rely 🙂
I thought Judith was a favorite.
[…] wrote a few weeks ago about the nagging problem of the measurement of temperature. The basic weather data are collected […]