Guest post by Willis Eschenbach
One of the claims in this hacked CRU email saga goes something like “Well, the scientists acted like jerks, but that doesn’t affect the results, it’s still warming.”
I got intrigued by one of the hacked CRU emails, from the Phil Jones and Kevin Trenberth to Professor Wibjorn Karlen. In it, Professor Karlen asked some very pointed questions about the CRU and IPCC results. He got incomplete, incorrect and very misleading answers. Here’s the story, complete with pictures. I have labeled the text to make it clear who is speaking, including my comments.
From Jones and Trenberth to Wibjorn Karlen, 17 Sep 2008 (email # 1221683947).
[Trenberth]Hi Wibjorn
It appears that your concern is mainly with the surface temperature record, and my co lead author in IPCC, Phil Jones, is best able to address those questions. However the IPCC only uses published data plus their extensions and in our Chapter the sources of the data are well documented, along with their characteristics. I offer a few more comments below (my comments are limited as I am on vacation and away from my office).
[Karlen to Trenberth]Uppsala 17 September 2008,
Dear Kevin,
In short, the problem is that I cannot find data supporting the temperature curves in IPCC and also published in e.g. Forster, P. et al. 2007: Assessing uncertainty in climate simulation. Nature 4: 63-64.
[My comments] Here is the figure from Nature, Assessing uncertainty in climate simulations, Piers Forster et al., Nature Reports Climate Change , 63 (2007) doi:10.1038/climate.2007.46a
Original Caption: Figure 1: Comparison of observed continental- and global-scale changes in surface temperature with results simulated by climate models using natural and anthropogenic forcings. Decadal averages of observations are shown for the period 1906 to 2005 (black line) plotted against the centre of the decade and relative to the corresponding average for 1901–1950. Lines are dashed where spatial coverage is less than 50%. Blue shaded bands show the 5–95% range for 19 simulations from five climate models using only the natural forcings due to solar activity and volcanoes. Red shaded bands show the 5–95% range for 58 simulations from 14 climate models using both natural and anthropogenic forcings. SOURCE: http://www.nature.com/climate/2007/0709/full/climate.2007.46a.html
Here is the IPCC figure he is referring to, Fig. 9.12, once again with the black lines showing the instrumentally measured temperatures:
Original Caption: Figure 9.12. Comparison of multi-model data set 20C3M model simulations containing all forcings (red shaded regions) and containing natural forcings only (blue shaded regions) with observed decadal mean temperature changes (°C) from 1906 to 2005 from the Hadley Centre/Climatic Research Unit gridded surface temperature data set (HadCRUT3; Brohan et al., 2006). The panel labelled GLO shows comparison for global mean; LAN, global land; and OCE, global ocean data. Remaining panels display results for 22 sub-continental scale regions (see the Supplementary Material, Appendix 9.C for a description of the regions).
Note that around the globe, temperatures are shown as rising from 1900 to about 1930, falling or staying level until the mid ’70s, and then rising sharply after that.
So these are the curves that Professor Karlen is attempting to reconstruct. Note that the IPCC chapter identifies these as “sub-continental regions” and shows separate data for ocean regions.
[Karlen] In attempts to reconstruct the temperature I find an increase from the early 1900s to ca 1935, a trend down until the mid 1970s and so another increase to about the same temperature level as in the late 1930s.
A distinct warming to a temperature about 0.5 deg C above the level 1940 is reported in the IPCC diagrams. I have been searching for this recent increase, which is very important for the discussion about a possible human influence on climate, but I have basically failed to find an increase above the late 1930s.
[Trenberth] This region, as I am sure you know, suffers from missing data and large gaps spatially. How one covered both can greatly influence the outcome.
In IPCC we produce an Arctic curve and describe its problems and character. In IPCC the result is very conservative owing to lack of inclusion of the Arctic where dramatic decreases in sea ice in recent years have taken place: 2005 was lowest at the time we did our assessment but 2007 is now the record closely followed by 2008.
Anomalies of over 5C are evident in some areas in SSTs but the SSTs are not established if there was ice there previously. These and other indicators show that there is no doubt about recent warming; see also chapter 4 of IPCC.
[My comment] As I will show below, everything he says about the ocean and the sea ice and the sea surface temperatures (SSTs) is meaningless. The IPCC figure is solely for the land.
[Karlen] In my letter to Klass V I included diagram showing the mean annual temperature of the Nordic countries (1890-ca 2001) presented on the net by the database NORDKLIM, a joint project between the meteorological institutes in the Nordic countries. Except for Denmark, the data sets show an increase after the 1970s to the same level as in the late 1930s or lower. None demonstrates the distinct increase IPCC indicates. The trends of these 6 areas are very similar except for a few interesting details.
[Trenberth] Results will also depend on the exact region.
[My comments] I cannot find the NORDKLIM graphic he refers to, so I have calculated it myself. I used the NORDKLIM dataset available at http://www.smhi.se/hfa_coord/nordklim/data/Nordklim_data_set_v1_0_2002.xls. I removed the one marine record from “Ship M”. To avoid infilling where there are missing records, I took the “first difference” of all of the available records for each year and averaged them. Then I used a running sum to calculate the average anomaly. I did not remove cities or adjust for the Urban Heat Island (UHI) effect. Here is the result:
You can see that, as Professor Karlen said, this does not show what the “Northern Europe” part of the IPCC graph shows. It is exactly as Professor Karlen stated, in the NORDKLIM data it rises until 1930, there is a drop from 1930 to 1970, followed by an increase after the 1970s to a temperature slightly lower than the 1930s. (In fact, the rise from 1880 until 1930 dwarfs the recent rise since the 1970’s). Here, for comparison, is a blowup of the “Northern Europe” graph from Fig. 9.12 above:
This claims that there is a full degree temperature rise from 1970 to 2000, ending way warmer than the 1930s. You can see why Professor Karlen is wondering how the IPCC got such a different answer.
[Karlen] I have in my studies of temperatures also checked a number of areas using data from NASA. One, in my mind interesting study, includes all the 13 stations with long and decent continuously records north of 65 deg N.
The pattern is the same as for the Nordic countries. This diagram only shows 11-yr means of individual stations. A few stations such as Verhojans and Svalbard indicate a recent mean 11-year temperature increase up to 0.5 deg C above the late 1930s. Verhojansk, shows this increase but the temperature has after the peak temperature decreased with about 0.3 deg C during the last few years. The majority of the stations show that the recent temperatures are similar to the one in the late 1930s.
In preparation of some talks I have been invited to give, I have expanded the Nordic area both west and east. The area of similar change in climate is vast. Only a few stations near Bering Strait deviates (e.g. St Paul, Kodiak, Nome, located south of 65 deg. N).
My studies include Africa, a study which took me most of a summer because there are a large number of stations in the NASA records. I found 11 stations including data from 1898-1975 and 16 stations including 1950-2003.
The data sets could in a convincing way be spliced. However, I noticed that some persons were not familiar with ‘splicing’ technique so I have accepted to reduce the study to the 7 stations including data from the whole period between 1898-2003. The results are similar as to the spliced data set andalso, surprisingly similar to the variability of the Nordic data.
Regression indicates a minor (if any) decrease in temperature (I have used all stations independent of location, city location or not).
[Trenberth] Africa is notorious for missing and inaccurate data and needs careful assessment.
[Karlen] Another example is Australia. NASA only presents 3 stations covering the period 1897-1992. What kind of data is the IPCC Australia diagram based on?
If any trend it is a slight cooling. However, if a shorter period (1949-2005) is used, the temperature has increased substantially.
The Australians have many stations and have published more detailed maps of changes and trends. There are more examples, but I think this is much enough for my present point:
How has the laboratories feeding IPCC with temperature records selected stations?
[Trenberth] See our chapter and the appendices.
[My comment] I have looked at these. The source for Fig. 9.1.2 is given as “(HadCRUT3; Brohan et al., 2006)”. HadCRUT3 is produced jointly by CRU and the Hadley Centre.
[Karlen] I have noticed that major cities often demonstrate a major urban effect (Buenos Aires, Osaka, New York Central Park, etc). Have data from major cities been used by the laboratories sending data to IPCC? Lennart Bengtsson and other claims that the urban effect is accounted for but from what I read, it seems like the technique used has been a simplistic
[Trenberth] Major inner cities are excluded: their climate change is real but very local.
[My comment] It is true that the IPCC Chapter 3 FAQ says this:
Additional warming occurs in cities and urban areas (often referred to as the urban heat island effect), but is confined in spatial extent, and its effects are allowed for both by excluding as many of the affected sites as possible from the global temperature data and by increasing the error range (the blue band in the figure).
To check this claim, I took the list of temperature stations used by CRU (which I had to use an FOI to get), and checked them against the GISS list. The GISS list categorizes stations as “Urban” or “Rural”. It also uses satellite photos to categorize the amount of light that shows at night, with big cities being brightest. It puts them into three categories, A, B, and C. C is the brightest.
It turns out that there are over 500 cities in the CRU database that the GISS database categorizes as “Urban C”, the brightest of cities. These include, among many others:
AUCKLAND, NEW ZEALAND
BANGKOK METROPOLIS, THAILAND
BARCELONA, SPAIN
BEIJING, CHINA
BRASILIA, BRAZIL
BRISBANE, AUSTRALIA
BUENOS AIRES, ARGENTINA
CHRISTCHURCH, NEW ZEALAND
DHAKA, BANGLADESH
FLORENCE, ITALY
GLASGOW, UK
GUATEMALA CITY, GUATEMALA
HANNOVER, GERMANY
INCHON, KOREA
KHARTOUM, SUDAN
KYOTO, JAPAN
LISBON, PORTUGAL
LUXOR, EGYPT
MARRAKECH, MOROCCO
MOMBASA, KENYA
MOSKVA, RUSSIAN FEDERA
MOSUL, IRAQ
NAGASAKI, JAPAN
NAGOYA, JAPAN
NICE, FRANCE
OSAKA, JAPAN
PRETORIA, SOUTH AFRICA
RIYADH, SAUDI ARABIA
SAO PAULO, BRAZIL
SEOUL, KOREA
SHANGHAI, CHINA
SINGAPORE, SINGAPORE
STOCKHOLM, SWEDEN
TEGUCIGALPA, HONDURAS
TOKYO, JAPAN
VALENCIA, SPAIN
VOLGOGRAD, USSR
So the CRU is using Tokyo? Beijing? Seoul? Shanghai? Moscow? Their claim is entirely false. In other words, once again the good folk of the CRU are blowing smoke. I can understand why it took me a Freedom of Information request to get the station list.
[Karlen] Next step has been to compare my results with temperature records in the literature. One interesting figures is published by you in:
Trenberth, K., 2005: Uncertainty in Hurricanes and Global Warming. Science 308: 1753-1754.
As you obviously know, the recent increase in temperature above the 1940s is minor between 10 deg N and 20 deg N and only slightly larger above the temperature maximum in the early 1950s. Both the increases in temperature in the 1930s and in the 1980s to 1990s is of similar amplitude and similar steepness, if any difference possibly slightly less steep in the northern area than in the southern (the eddies slow down the warm water transport).
Your diagram describes a limited area of the North Atlantic because you are primarily interested in hurricanes. The complexity of sea surface temperature increases and decreases is seen in e.g. Cabanes, C, et al 2001 (Science 294: 840-842).
[Trenberth] As we discuss, there is a lot of natural variability in the North Atlantic but there is also a common component that relates to global changes. See my GRL article with Shea for more details. Trenberth, K. E., and D. J. Shea, 2006: Atlantic hurricanes and natural variability in 2005. Geophys. Res. Lett., 33, L12704, doi:10.1029/2006GL026894.
[Karlen] One example of sea surface temperature is published by:
Goldenberg, S.B., Landsea, C.W., Mestas-Nuoez, A.M. and Gray, W.M., 2001: The recent increases in Atlantic hurricane activity: causes and implications. Science 293: 474-479.
Again, there is a marked increase in temperature in the 1930s and 1950s (about 1 deg C), a decrease to approximately the level in the 1910s and thereafter a new increase to a temperature slightly below the level in the1940s.
One example of published data not supporting a major temperature increase during recent time is: Polyakov, I.V., Bekryaev, R.V., Alekseev, G.H., Bhatt,U.S., Colony, R.L., Johnson, M.A., Maskshtas, A.P. and Walsh, D., 2003: Variability and Trends of Air Temperature and Pressure in the Maritime Arctic, 1875-2000. Journal of Climate: Vol. 16 (12): 2067ñ2077.
He included many more stations than I did in my calculation of temperatures N 65 N, but the result is similar. It is hard to find evidence of a drastic warming of the Arctic.
It is also difficult to find evidence of a drastic warming outside urban areas in a large part of the world outside Europe. However the increase in temperature in Central Europe may be because the whole area is urbanized (see e.g. Bidwell, T., 2004: Scotobiology – the biology of darkness. Global change News Letter No. 58 June, 2004).
So, I find it necessary to object to the talk about a scaring temperature increase because of increased human release of CO2. In fact, the warming seems to be limited to densely populated areas. The often mentioned correlation between temperature and CO2 is not convincing. If there is a factor explaining a major part of changes in the temperature, it is solar irradiation. There are numerous studies demonstrating this correlation but papers are not accepted by IPCC. Most likely, any reduction of CO2 release will have no effect whatsoever on the temperature (independent of how expensive).
[Trenberth] You can object all you like but you are not looking at the evidence and you need to have a basis, which you have not established. You seem to doubt that CO2 has increased and that it is a greenhouse gas and you are very wrong. But of course there is a lot of variability and looking at one spot narrowly is not the way to see the big picture.
[My comment] Professor Karlen was quite correct. The claims made by the CRU, and repeated in the IPCC document, were false. Karlen was looking at the evidence.
[Karlen] In my mind, we have to accept that it is great if we can reduce the release of CO2 because we are using up a resource the earth will be short of in the future, but we are in error if we claims a global warming caused by CO2.
[Trenberth] I disagree.
[My comment] No comment.
[Karlen] I also think we had to protest when erroneous data like the claim that winter temperature in Abisko increased by 5.5 deg C during the last 100 years. The real increase is 0.4 deg C. The 5.5 deg C figure has been repeated a number of times in TV-programs. This kind of exaggerations is not supporting attempts to save fossil fuel.
I have numerous diagrams illustrating the discussion above. I don’t include these in an e-mail because my computer can only handle a few at a time. If you would like to see some, I can send them by air mail.
I am often asked about why I don’t publish about my views. I have. Just one example of among 100 other I could select is: Karlen, W., 2001: Global temperature forces by solar irradiation and greenhouse gases? Ambio 30(6): 349-350.
Yours sincerely
Wibjorn,
[Trenberth] I trust that Phil Jones may also respond
From: P.Jones
To: trenbert
Subject: Re: Climate
Date: Wed, 17 Sep 2008 16:39:07 +0100 (BST)
Cc: Wibjorn Karlen
[Jones to Professor Karlen, same email]Wibjorn,
I’m in Athens at the moment. Unless you’re referring specifically to the Arctic the temperature curves in IPCC Ch 3 all include the oceans.
[My comment] Absolutely not. The legend for Fig. 9.1.2 (see above) says “(see the Supplementary Material, Appendix 9.C for a description of the regions)” Appendix 9.C in turn describes the calculations:
6. Apply land/ocean mask on observations. Plots describing observed changes in land or ocean areas were based on observed data that was masked to retain land or ocean data only (necessary to remove islands and marine stations not existent in models). This masking was performed as in Step 3, using the land area fraction data from the CCSM3 model.
Note that the ocean is entirely masked out of the observations.
And the regions are described as:
Note 2: List of Regions
The regions are defined as the collection of rectangular boxes listed for each region. The domain of interest (land and ocean, land, or ocean) is also given.
REGION, DESIGNATOR, COVERAGE, DOMAIN
Global, GLO, 180W to 180E, 90S to 90N, land and ocean
Global Land, LAN, 180W to 180E, 90S to 90N, land
Global Ocean, OCE, 180W to 180E, 90S to 90N, ocean
North America, ALA, 170W to 103W, 60N to 72N, land
North America, CGI, 103W to 10W, 50N to 85N, land
North America, WNA, 130W to 103W, 30N to 60N, land
North America, CNA, 103W to 85W, 30N to 50N, land
North America, ENA, 85W to 50W, 25N to 50N, land
South America, CAM, 116W to 83W, 10N to 30N, land
South America, AMZ, 82W to 34W, 20S to 12N, land
South America, SSA, 76W to 40W, 56S to 20S, land
Europe, NEU, 10W to 40E, 48N to 75N, land
Europe, SEU, 10W to 40E, 30N to 48N, land
Africa, SAR, 20W to 65E, 18N to 30N, land
Africa, WAF, 20W to 22E, 12S to 18N, land
Africa, EAF, 22E to 52E, 12S to 18N, land
Africa, SAF, 10E to 52E, 35S to 12S, land
Asia, NAS, 40E to 180E, 50N to 70N, land
Asia, CAS, 40E to 75E, 30N to 50N, land
Asia, TIB, 75E to 100E, 30N to 50N, land
Asia, EAS, 100E to 145E, 20N to 50N, land
Asia, SAS, 65E to 100E, 5N to 30N, land
Asia, SEA, 95E to 155E, 11S to 20N, land
Australia, NAU, 110E to 155E, 30S to 11S, land
Australia, SAU, 110E to 155E, 45S to 30S, land
So no, that excuse won’t wash. Once again Professor Karlan is quite correct. The observations simply don’t match the CRU/IPCC claims. Phil Jones’ story about the regions including the ocean is false.
[Jones] Fennoscandia is just a small part of the NH. When I’m back next week, I’ll be able to calculate the boxes that encompass Fennoscandia, so you can compare with this region. As you’re aware Anders did lots of the update work in 2001-2002 and he included all the NORDKLIM data. I can send you a list of the Fennoscandian data if you want – either the sites used or their data as well.
I guess you’re attachments are in your direct email, which I come to later.
One final thing – we are getting SST data in from some of the new sea-ice free parts of the Arctic. We are not using these as we’ve yet to figure out how to as we don’t have normals for these ‘mostly covered by sea ice in the 1961-90’ areas.
Cheers
Phil
[My comments]Now, I have not taken a stand on whether the machinations of the CRU extended to actually altering the global temperature figures. It seems quite clear from Professor Karlen’s observations, however, that they have gotten it very wrong in at least the Fennoscandian region. Since this region has very good records and a lot of them, this does not bode well for the rest of the globe …
My best to everyone,
w.
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Thomas Johnson (22:45:37) :
…….
My grandson has been required to sit through Mr Gore’s movie three times this school year.
I hope you are in the US – if you are in the UK then the school has broken the law. The UK High Court found that Gore’s film was nothing better than Party Political Propaganda with 11 major factual mistakes that made it WRONG.
Perhaps those of you in the US should try & use the UK High Court’s decision to at least force the schools to stop / cut down on the political propaganda ?
bill (17:24:04) :
Bill, you raise a good question. Using the derivative is called the “first difference” method. If you don’t use it you get erroneous results. See Peterson for a full explanation.
w.
Willis:
1. I assume the graphic you object to is marked NEU. If this refers to northern Europe then the data you reference does not include much of N.Europe. From my investigation the 1935 hump decreases with measurements further south. So NEurope I would assume include GB, N France Genmany Netherlands etc. These are not included in your referenced data source.
If these were included the hump wou;d reduce!
2. Method:
I removed the one marine record from “Ship M”. To avoid infilling where there are missing records, I took the “first difference” of all of the available records for each year and averaged them. Then I used a running sum to calculate the average anomaly. I did not remove cities or adjust for the Urban Heat Island (UHI) effect. Here is the result
This does not seem to explain how you obtained anomaly, and averaging the derivative over the year seems to be a bit dubious – to start with you are throwing away the monthly data very early on in the analysis.
The method I used:
1. For each of the reference years (1961 to 1990) average all available months data (eg average [jan 1961, jan1962, … jan 1990]) Obviously missing data will change this average fractionally – in the data you referenced the worst station over this ref period returned 20 measurements.
2. Each months data for a station has the reference month (1961 to 1990) subtracted to give the monthly anomaly.
3. All reporting stations are then averaged month by month.
4. A moving average is then applied to the monthly average. Any missing average causes a non plot of +-0.5 of the moving average period (this also terminates plotting at the ends of the record)
This method retains full monthly granularity up to the time the moving average is applied. No infilling is performed. Missing data causes minor errors in averaging but no assumptions (as with infilling are made)
This method seems sound to me and plot outputs are between yours and ipcc’s.
Using derivatives on very noisy data seems like a problem to me!
How about these facts? Where’s the email that changes the chemistry of the elements and sources involved?
How do we know that recent CO2 increases are due to human activities?
Filed under: Climate Science FAQ Greenhouse gases Paleoclimate — eric @ur momisugly 22 December 2004 – () ()
Note:This is an update to an earlier post, which many found to be too technical. The original, and a series of comments on it, can be found here. See also a more recent post here for an even less technical discussion.
Over the last 150 years, carbon dioxide (CO2) concentrations have risen from 280 to nearly 380 parts per million (ppm). The fact that this is due virtually entirely to human activities is so well established that one rarely sees it questioned. Yet it is quite reasonable to ask how we know this.
One way that we know that human activities are responsible for the increased CO2 is simply by looking at historical records of human activities. Since the industrial revolution, we have been burning fossil fuels and clearing and burning forested land at an unprecedented rate, and these processes convert organic carbon into CO2. Careful accounting of the amount of fossil fuel that has been extracted and combusted, and how much land clearing has occurred, shows that we have produced far more CO2 than now remains in the atmosphere. The roughly 500 billion metric tons of carbon we have produced is enough to have raised the atmospheric concentration of CO2 to nearly 500 ppm. The concentrations have not reached that level because the ocean and the terrestrial biosphere have the capacity to absorb some of the CO2 we produce.* However, it is the fact that we produce CO2 faster than the ocean and biosphere can absorb it that explains the observed increase.
Another, quite independent way that we know that fossil fuel burning and land clearing specifically are responsible for the increase in CO2 in the last 150 years is through the measurement of carbon isotopes. Isotopes are simply different atoms with the same chemical behavior (isotope means “same type”) but with different masses. Carbon is composed of three different isotopes, 14C, 13C and 12C. 12C is the most common. 13C is about 1% of the total. 14C accounts for only about 1 in 1 trillion carbon atoms.
CO2 produced from burning fossil fuels or burning forests has quite a different isotopic composition from CO2 in the atmosphere. This is because plants have a preference for the lighter isotopes (12C vs. 13C); thus they have lower 13C/12C ratios. Since fossil fuels are ultimately derived from ancient plants, plants and fossil fuels all have roughly the same 13C/12C ratio – about 2% lower than that of the atmosphere. As CO2 from these materials is released into, and mixes with, the atmosphere, the average 13C/12C ratio of the atmosphere decreases.
Isotope geochemists have developed time series of variations in the 14C and 13C concentrations of atmospheric CO2. One of the methods used is to measure the 13C/12C in tree rings, and use this to infer those same ratios in atmospheric CO2. This works because during photosynthesis, trees take up carbon from the atmosphere and lay this carbon down as plant organic material in the form of rings, providing a snapshot of the atmospheric composition of that time. If the ratio of 13C/12C in atmospheric CO2 goes up or down, so does the 13C/12C of the tree rings. This isn’t to say that the tree rings have the same isotopic composition as the atmosphere – as noted above, plants have a preference for the lighter isotopes, but as long as that preference doesn’t change much, the tree-ring changes wiil track the atmospheric changes.
Sequences of annual tree rings going back thousands of years have now been analyzed for their 13C/12C ratios. Because the age of each ring is precisely known** we can make a graph of the atmospheric 13C/12C ratio vs. time. What is found is at no time in the last 10,000 years are the 13C/12C ratios in the atmosphere as low as they are today. Furthermore, the 13C/12C ratios begin to decline dramatically just as the CO2 starts to increase — around 1850 AD. This is exactly what we expect if the increased CO2 is in fact due to fossil fuel burning. Furthermore, we can trace the absorption of CO2 into the ocean by measuring the 13C/12C ratio of surface ocean waters. While the data are not as complete as the tree ring data (we have only been making these measurements for a few decades) we observe what is expected: the surface ocean 13C/12C is decreasing. Measurements of 13C/12C on corals and sponges — whose carbonate shells reflect the ocean chemistry just as tree rings record the atmospheric chemistry — show that this decline began about the same time as in the atmosphere; that is, when human CO2 production began to accelerate in earnest.***
In addition to the data from tree rings, there are also of measurements of the 13C/12C ratio in the CO2 trapped in ice cores. The tree ring and ice core data both show that the total change in the 13C/12C ratio of the atmosphere since 1850 is about 0.15%. This sounds very small but is actually very large relative to natural variability. The results show that the full glacial-to-interglacial change in 13C/12C of the atmosphere — which took many thousand years — was about 0.03%, or about 5 times less than that observed in the last 150 years.
For those who are interested in the details, some relevant references are:
Stuiver, M., Burk, R. L. and Quay, P. D. 1984. 13C/12C ratios and the transfer of biospheric carbon to the atmosphere. J. Geophys. Res. 89, 11,731-11,748.
Francey, R.J., Allison, C.E., Etheridge, D.M., Trudinger, C.M., Enting, I.G., Leuenberger, M., Langenfelds, R.L., Michel, E., Steele, L.P., 1999. A 1000-year high precision record of d13Cin atmospheric CO2. Tellus 51B, 170–193.
Quay, P.D., B. Tilbrook, C.S. Wong. Oceanic uptake of fossil fuel CO2: carbon-13 evidence. Science 256 (1992), 74-79
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marky48 (08:28:34) says :
“How about these facts?”…
.
How do I get the three minutes of my life back for reading that pointless waste of time?
The central fact was never mentioned: that there is zero empirical evidence that carbon dioxide has any measurable effect on the planet’s temperature. Zip. Nada. None. ZE-RO.
When someone provides a real world, testable, reproducible and falsifiable experiment demonstrating a specifically measurable cause and effect between X amount of CO2 increase and X amount of warming, wake me. But so far, the ultimate authority — planet Earth — is cooling at the same time that harmless and beneficial CO2 rises.
In the mean time, arguing about the fluctuations in a tiny trace gas is a pointless waste of everyone’s time.
It is with a wizard like you there smokemon. I addressed this. You were even corrected by a member here. Look at the absorption number 781,000 and the annual increase 11,700. That’s half the human contribution. It ain’t rocket science.
Perhaps Herr Watts could address this since folks use this graph incorrectly. It’s about the net increase and the source.
Well, maybe is is rocket science?
http://climate.nasa.gov/Eyes/
What do you guys use for your measurements?
[snip] says “As I understand it, and please correct me if I am wrong, the GHG emmissions from the eruptions of Mt St Hellens and Pintatubo exceded the total of human emissions by a factor of many times”
That is completely wrong. The largest amount of volcanic GHG, water vapor, emitted by Pinatubo (491 Mt) was far less than the 20,000 Mt of water vapor emitted by fossil fuel burning each year. The story with CO2 is even more wrong: 42 Mt of CO2 from Pinatubo versus 150,000 Mt natural and 7100 Mt manmade CO2 annually.
In reply to post re temperatures in Finland in July – I’ve just checked Wikepedia
(cos Iwouln’t have a clue otherwise) and it says that July and early August 25 to 30 degrees occurs on the ‘warmest days’ of that period. so I guess that means Finland could have a 23 degree average for July, doesn’t it? I guess it depends how many warm days in the month?
If anyone out there can do maths or understands this please comment.
confused but riveted
re Finland in July temperatures, I was commenting on post by pd
That same Wikipaedia entry says Finland is gaining territory at a rate of 7km a year through ice. Huh? I thought the stuff was supposed to be melting and drowning little islands – is it actually going to Finland?
The obvious is now evident. What can the non scientific based community of ‘non believers’ do now?
I am surrounded by those who quietly doubt but would never ripple the waters by being open about it.
It is clear that some of the recording sites were chosen for their readings to be higher ie close to reflected or man made heat sources etc. as well as the fudge factors, built in adjustments etc.
Stay strong but help us – who are not experts. Your website is excellent, and challenging as it should be.
Does this argument hold water without implicitly accusing a large number of scientists of being liars?
Karlen is arguing that he can’t reconstruct the european trend. First observation: the inability of a particular person to reconstruct a result does not imply the result is invalid.
Instead, let’s search the literature for other reconstructions which support the IPCC graphs. A quick method: search Google Scholar for “european temperature reconstruction”.
European Seasonal and Annual Temperature Variability, Trends, and Extremes Since 1500 – all by researchers at the University of Bern, Switzerland.
That’s the top hit. Of course not all of them have much to say on the issue, and few have more than abstracts on-line. But just try to find one that agrees with Karlen.
Unpublished findings mean nothing – even if you can get them published in a vanity journal, that is better than nothing. All you’ve found here is the confused questions of a researcher. Did he publish this finding? Or did it just die, and Karlen stop responding once he figured it out…
Sam, we don’t need multiproxy reconstructions, we need the temperature records for a direct comparison. To say “unpublished findings mean nothing” is to assert that questions mean nothing. In fact, the unadjusted temp graph result HAS been published – here. No net warming over mid20th century.
We are now seeing reviews and challenges in these areas – Alaska, England, United States, Australia (Darwin), New Zealand, Finland, Hawaii, South America.
We see the satellite doesnt match the surface records.
We have the CRU Team admit that land temp increases are 2X the sea changes since 1970s.
We are seeing these biases/errors – Neglect/mal-adjustment of Urban heat Island effect; IPCC claiming they are not using urban stations when they are; adjustments ‘out of thin air’ or in some cases (eg case of GrandCanyon) inappropriately adding to the warming trend of rural stations to match urban trend (!!); movement of stations and removal of colder/high altitude stations (eg removal of Bolivia). All these biases and errors amazingly go in one direction – they magnify the warming.
We know also that in the past 70 years, there was no more than 0.5C temp increase. A mere 0.005C/yr bias could triple the amount of warming versus 1940. If the Nordic case were replicated on the global level, the entire “signature” for man-made warming would be an artifact of bad adjustments. Where is the proof and validation that this is not happening?
The 20th century global temperature record has apparently been tampered with, and cannot be trusted unless and until a thorough review of the adjustments applied to it has been conducted.
Rubbish. It’s already been shown that the anomaly found using only the highest-quality stations in the US comes up with an almost identical result for the one where you do include them, thus validating their method of removing the signature of the UHI from the data.
I’m following the challenges in New Zealand, and they are a dishonest attempt by a well-known pack to discredit the NIWA. Claims that the unadjusted data and method of adjustment were not available have turned out to be unfounded.
But there are other ways we can confirm that the planet is warming than the temperature record. The retreat of glaciers, for instance. Changes in times of the year that spring starts. Changes in migratory patterns. These all point towards one inescapable conclusion – that the world is warming dramatically, we’re responsible, and there is much more warming in store.
Sam Vilain,
Lotsa opinion there, but no facts.
Next, these climatologists will be telling us that we’re responsible for the decline in sunspot activity.
Smokey, you calling me on my facts?
The NOAA response to SurfaceStations.org claims finds;
That is a fact. They ran the figures with all of the sites which were identified as “best” in the SurfaceStations.org survey, and what do you know – the results were just the same.
There’s a bit of a round-up of the dishonesty at OpenParachute on the NIWA debacle.
Finally, this section of Wikipedia is a nice summary of the wide range of physical evidence that I refer to. You’ll see that section is quite thoroughly referenced.
[REPLY – I can’t say anything about this issue for now, except that the NOAA’s conclusions are fatally flawed and they have failed to take something vital into account that I cannot yet discuss. All I can do is ask your patience. The issue will be addressed. ~ Evan]
Sam Villain
The problem with that NOAA report is that the methodology is not published. It appears that the data from those “best” sites was homogenized adjusted data so they didn’t compare apples to oranges, they compared the apple to the same apple.
Sam Villain,
I think you answered or someone else did but it seems some posts got inadvertently deleted and it may have been accidentally deleted, it may even have been my fault, if so, I apologize and please repost.
You put up some quotes about some methodology but you appear to be conflating papers and responses. To see what happened in the response from NOAA to the surface stations project please read this post on CA. No methodologies or provenance of data were disclosed in any usable way and it was not a peer reviewed study.
Sam: ” Neglect/mal-adjustment of Urban heat Island effect;””Rubbish. It’s already been shown that the anomaly found using only the highest-quality stations in the US comes up with an almost identical result for the one where you do include them,”
Show us the peer-reviewed papers on this, including the raw and adjusted data to back it up, so we know this isn’t a snow job.
Meanwhile, let’s hear the cover story on the Wang and Jones flawed/fraud paper and their dishonest treatment of UHI.
“thus validating their method of removing the signature of the UHI from the data.”
… as stated by Jeez, they have apparently compared their own results to their own results and found they match. Show us the UNADJUSTED data that they started with.
“I’m following the challenges in New Zealand, and they are a dishonest attempt by a well-known pack to discredit the NIWA. Claims that the unadjusted data and method of adjustment were not available have turned out to be unfounded.”
Show us the peer-reviewed papers on this, including the raw and adjusted data to back it up, so we know this isn’t a snow job. What is YOUR unadjusted trend?
“But there are other ways we can confirm that the planet is warming than the temperature record. The retreat of glaciers, for instance. Changes in times of the year that spring starts. ”
Spring starts Mar 21 every year. If the temps are higher, then the thermometer would record it.
I’ve looked at the unadjusted top 10% longest-running global land temp records, about 1300 records running over 100 years apiece. This unadjusted data shows and average 2000-2009 temperature that is less than 0.1C higher than 1930-1939.
“Changes in migratory patterns. These all point towards one inescapable conclusion – that the world is warming dramatically, we’re responsible, and there is much more warming in store.”
Non-temperature anecdotes not only are a poor substitute for the historical temperature record, it’s quite laughable to insist that past history can not only dictates temperatures, but can dictate responsibility for them and future trends.
That’s not science, that’s ASTROLOGY!
Er, sure – I linked to the peer reviewed study which described the methodology used in constructing the GISS series. That’s what this is about, right? Why would they have to republish it if it’s already been in the literature since 1996? They’re just running the same method with a smaller data set. Just search Google Scholar for “Gistemp” and you should find it. I can’t find the original paper I linked, but this page seems to go through it in far more detail.
And Evan – you just keep telling yourself those results are flawed. Maybe someday, you’ll believe it.
Here is the original study I linked to:
Hansen, J., R. Ruedy, M. Sato, M. Imhoff, W. Lawrence, D. Easterling, T. Peterson, and T. Karl (2001), A closer look at United States and global surface temperature change, J. Geophys. Res., 106(D20), 23,947–23,963.
Yay for backtype.
None of which is relevant for their new and improved homogenized datasets.
Please read the link I put up in the last post.
The exchange of data sets and relevant URL’s between opposing sets of scientists bewilders a skeptical but untrained observer like myself. I see something like eighteenth century warfare at work: lines of opposing musketeers exchanging volley after volley, standing firm and determined, filling holes torn in the forward ranks with willing soldiers from the back ranks stepping forward. Which line’s discipline will break first? Bewildering.
My distinctly untrained conclusions:
1) Any scientific basis AGW proponents could lay claim to stands discredited and should be rejected. Even the work of honorable scientists bears the taint.
2) Therefore, no reasonable basis exists to disembowel first world industrial economies to assuage AGW’s unfounded and hysterically reiterated ad nauseam fears. These fears have no scientific foundation of merit, just lots and lots of perjured data pushing a leftist political agenda.
3) Copenhagen’s misspent efforts would bear better results if directed at attainable reductions in pollutants and pursuit of economically viable energy sources.
4) Science should punch ‘reset’ on climate research. An independent board (and, for God’s sake, no UN involvement!) should establish strict protocols insuring complete transparency of all research–raw data to finished papers–and let the right consensus emerge honestly and in front of interested observers like myself. After all, we little people now stand on notice that the benefits and costs all devolve on us in the end.
I only hope the world gets the chance to do something like this; inertia in favor of AGW policies has such power now–it seems that the broken vessel bearing their misbegotten dreams for control of the world can drift into safe harbor no matter what alarmed and angry passengers do by way of storming the wheelhouse. Is it too late?
Note: In Denmark is used several billions to increase the temperature in the rural landscapes for better agriculture.
“As a consequence of these planting activities, around 800 km of shelterbelts were planted yearly until the 1990s and the total forest area in Jutland tripled from 100,000 ha in 1881 to 300,000 ha in 2000, of which 85% consists of coniferous plantations.”
Runcible, that might be the case, except the argument is simply too strong, it’s gone on for too long. For over 100 years the debate raged in the scientific community. All the major challenges have been tested and failed.
A few sceptics’ inability to follow what the professionals are doing is hardly call to delay action.
Jeez, I’ve looked at your link and again I just don’t see how it supports your position that a different method of correction is used. I’ll try again later perhaps.
Not.
GISS Surface Temperature Analysis
Station List Search: (60.3 N,16.1 E)
Stations are ordered by distance from center at (60.3 N,16.1 E). Click the “(*)” next to a station name and the list will be re-sorted by distance from that station.
Distance Station Name Lat Lon ID Pop. Years
92 km (*) Uppsala 59.9 N 17.6 E 645024580000 157,000 1880 – 1970
92 km (*) Uppsala 59.9 N 17.6 E 645024580001 157,000 1961 – 1970
120 km (*) Orebo Sweden 59.3 N 15.2 E 645024390010 171,000 1880 – 1907
149 km (*) Stockholm 59.3 N 18.1 E 645024640000 1,357,000 1880 – 1980
149 km (*) Stockholm 59.3 N 18.1 E 645024640001 1,357,000 1949 – 1990
149 km (*) Stockholm 59.3 N 18.1 E 645024640002 1,357,000 1951 – 1991
149 km (*) Stockholm 59.3 N 18.1 E 645024640003 1,357,000 1971 – 1980
149 km (*) Stockholm 59.3 N 18.1 E 645024640004 1,357,000 1987 – 1994
180 km (*) Karlstad Flyg 59.4 N 13.5 E 645024180000 51,000 1951 – 1991
180 km (*) Karlstad Flyg 59.4 N 13.5 E 645024180001 51,000 1977 – 1990
180 km (*) Karlstad Flyg 59.4 N 13.5 E 645024180002 51,000 1987 – 2008
210 km (*) Maarianhamina Finland 60.1 N 19.9 E 614029710010 rural area 1961 – 1981
275 km (*) Vastervik Sweden 57.8 N 16.6 E 645025760010 21,000 1880 – 1907
278 km (*) Harnosand Sweden 62.6 N 18.0 E 645023610010 19,000 1880 – 1991
280 km (*) Oslo/Gardermo 60.2 N 11.1 E 634013840000 rural area 1951 – 1991
280 km (*) Oslo/Gardermo 60.2 N 11.1 E 634013840001 rural area 1960 – 1990
280 km (*) Oslo/Gardermo 60.2 N 11.1 E 634013840002 rural area 1961 – 1980
280 km (*) Oslo/Gardermo 60.2 N 11.1 E 634013840003 rural area 1986 – 2009
302 km (*) Jonkoping Fly 57.8 N 14.1 E 645025500000 131,000 1951 – 1991
302 km (*) Jonkoping Fly 57.8 N 14.1 E 645025500001 131,000 1974 – 1990
302 km (*) Jonkoping Fly 57.8 N 14.1 E 645025500002 131,000 1971 – 1980
302 km (*) Jonkoping Fly 57.8 N 14.1 E 645025500003 131,000 1987 – 2009
305 km (*) Oslo/Blindern 59.9 N 10.7 E 634014890010 645,000 1880 – 1991
305 km (*) Oslo/Blindern 59.9 N 10.7 E 634014890011 645,000 1961 – 1980
315 km (*) Visby Airport Sweden 57.7 N 18.4 E 645025900000 20,000 1951 – 1991
315 km (*) Visby Airport Sweden 57.7 N 18.4 E 645025900001 20,000 1949 – 1990
315 km (*) Visby Airport Sweden 57.7 N 18.4 E 645025900002 20,000 1961 – 1970
315 km (*) Visby Airport Sweden 57.7 N 18.4 E 645025900003 20,000 1971 – 1980
315 km (*) Visby Airport Sweden 57.7 N 18.4 E 645025900004 20,000 1987 – 2009
336 km (*) Ostersund/Fro 63.2 N 14.5 E 645022260000 14,000 1949 – 1990
336 km (*) Ostersund/Fro 63.2 N 14.5 E 645022260001 14,000 1951 – 1991
336 km (*) Ostersund/Fro 63.2 N 14.5 E 645022260002 14,000 1971 – 1980
336 km (*) Ostersund/Fro 63.2 N 14.5 E 645022260003 14,000 1961 – 1970
336 km (*) Ostersund/Fro 63.2 N 14.5 E 645022260004 14,000 1987 – 2009
338 km (*) Turku 60.5 N 22.3 E 614029720000 217,000 1951 – 1991
338 km (*) Turku 60.5 N 22.3 E 614029720001 217,000 1950 – 1990
338 km (*) Turku 60.5 N 22.3 E 614029720002 217,000 1971 – 1980
338 km (*) Turku 60.5 N 22.3 E 614029720003 217,000 1987 – 2009
344 km (*) Ferder Fyr 59.0 N 10.5 E 634014820000 rural area 1885 – 1955
360 km (*) Roros 62.6 N 11.4 E 634012880000 rural area 1880 – 1989
369 km (*) Goteborg/Save 57.8 N 11.9 E 645025120000 691,000 1951 – 1991
369 km (*) Goteborg/Save 57.8 N 11.9 E 645025120001 691,000 1977 – 1990
369 km (*) Goteborg/Save 57.8 N 11.9 E 645025120002 691,000 1971 – 1980
369 km (*) Goteborg/Save 57.8 N 11.9 E 645025120003 691,000 1987 – 2007
378 km (*) Torslanda 57.7 N 11.8 E 645025120010 691,000 1961 – 1970
407 km (*) Jokioinen 60.8 N 23.5 E 614029630000 rural area 1957 – 1991
407 km (*) Jokioinen 60.8 N 23.5 E 614029630001 rural area 1958 – 1990
407 km (*) Jokioinen 60.8 N 23.5 E 614029630002 rural area 1971 – 1980
407 km (*) Jokioinen 60.8 N 23.5 E 614029630003 rural area 1987 – 2009
415 km (*) Gaustatoppen Norway 59.9 N 8.7 E 634014500010 rural area 1934 – 1974
422 km (*) Fokstua Ii 62.1 N 9.3 E 634012380000 rural area 1923 – 2009
423 km (*) Skagen 57.7 N 10.6 E 612060410000 12,000 1880 – 1926
424 km (*) Dombas Norway 62.0 N 9.1 E 634012380010 rural area 1880 – 1976
426 km (*) Vaasa 63.1 N 21.6 E 614029120000 54,000 1950 – 1990
426 km (*) Vaasa 63.1 N 21.6 E 614029120001 54,000 1951 – 1991
426 km (*) Vaasa 63.1 N 21.6 E 614029120002 54,000 1971 – 1980
426 km (*) Vaasa 63.1 N 21.6 E 614029120003 54,000 1987 – 2001
432 km (*) Tampere 61.5 N 23.7 E 614029440010 221,000 1961 – 1970
439 km (*) Halmstad Sweden 56.7 N 12.9 E 645026200010 50,000 1880 – 1907
455 km (*) Baltischport Ussr 59.4 N 24.1 E 613260380010 rural area 1880 – 1880
457 km (*) Trondheim/Tyholt Norway 63.4 N 10.5 E 634012580010 135,000 1880 – 1981
465 km (*) Torungen Fyr 58.4 N 8.8 E 634014650000 rural area 1880 – 2009
476 km (*) Haugastol Norway 60.3 N 7.5 E 634013510010 rural area 1884 – 1976
488 km (*) Helsinki/Seutula 60.3 N 25.0 E 614029740000 794,000 1880 – 1991
488 km (*) Helsinki/Seutula 60.3 N 25.0 E 614029740001 794,000 1880 – 1980
488 km (*) Helsinki/Seutula 60.3 N 25.0 E 614029740002 794,000 1949 – 1990
488 km (*) Helsinki/Seutula 60.3 N 25.0 E 614029740003 794,000 1971 – 1980
488 km (*) Helsinki/Seutula 60.3 N 25.0 E 614029740004 794,000 1987 – 2009
493 km (*) Tallin 59.4 N 24.8 E 613260380000 430,000 1881 – 1990
493 km (*) Tallin 59.4 N 24.8 E 613260380001 430,000 1951 – 1991
493 km (*) Tallin 59.4 N 24.8 E 613260380002 430,000 1936 – 1989
493 km (*) Tallin 59.4 N 24.8 E 613260380003 430,000 1936 – 1989
493 km (*) Tallin 59.4 N 24.8 E 613260380004 430,000 1957 – 1990
493 km (*) Tallin 59.4 N 24.8 E 613260380005 430,000 1971 – 1980
493 km (*) Tallin 59.4 N 24.8 E 613260380006 430,000 1961 – 1970
493 km (*) Tallin 59.4 N 24.8 E 613260380007 430,000 1987 – 2009
Go to GISTEMP Station Selector