” It remains to be shown that there are sufficient errors in the data to significantly affect conclusions drawn from them.”
I’ll put you down as “not getting the point”.
When errors are found in a particular process, you need to correct the process or you are exposed to the risk of further errors due to flaws in the process. The process itself has been shown flawed and should be fixed. For more on this, you can look at for example books on Six Sigma Quality or works by Deming.
“Models indicate ...” models are not data.
“The data shows similar patterns.” The data cannot be trusted unless the processes used to derive them are corrected and shown to be so with full transparency.
“Remember that science is self-checking, in a lot of ways. “
It cannot be fully self-checking if data and data adjustment methodology is not made transparent. Yes, they publish papers, but they don’t publish the underlying data that enable true reproducibility. This was part of the ‘hockey stick’ controversy as well. The climate science community has been overly lax in not making sure results are truly reproducible.
“The graphs I posted show that 1934 was virtually as warm as 1998 in the U.S. The revision was very minor.” Another ‘missing the point’ comment.
“The U.S. has urbanized much more rapidly than other areas of the world.” LOL. This is certainly news to the billions now living in cities in Asia, Africa, and South America.
“Why does the data have to be “cleaner” just because we’re the United States?” — I am merely repeating statements from climate scientists that have stated as much.
If you want to believe that stations in Yemen and Sri Lanka are as well-maintained as US stations, go ahead, but unless a thorough review of station quality and temperature adjustment metrics is done, we cannot infer that global temp measurements are reliable to the precision required to say much about global warming. The potential signal to noise is too small.
“It remains to be shown that the true condition of the temperature stations substantially affects the quality of the data set.” -— So, unlike every other branch of science where skepticism reigns and nothings is assumed true unless proven so, AGW ‘science’ is assumed true unless proven false. Sweet. It’s a nice gig to have, but it’s not science!
Here is a quote that gets to the heart of (a) non-US temperature records such as these China records are non-reliable (b) why merely statements in published papers are not sufficienct (and often completely false) (c) why one small error is just the tip of the iceberg (d) temperature record consistency is a lot worse than climate science community has let on. From newsbusters, a post about the Keenan report:
http://newsbusters.org/blogs/noel-sheppard/2007/08/10/un-s-ipcc-accused-possible-research-fraud
As Keenan stated in his full report concerning this matter (emphasis added throughout):
Meteorological stations sometimes move, and this can affect the temperature measurements of the stations. For example, one of the stations relied upon by the above two papers was originally located on the upwind side of a city and later moved, 25 km, to be on the downwind side of the city. Such a move would be expected to increase the measured temperatures, because a city generates heat. Another station relied upon by the papers was originally located in the center of a city and then moved, 15 km, to be by the shore of a sea. Such a move would be expected to decrease the measured temperatures.
Those that have read the work of Anthony Watts at SurfaceStations.org certainly can understand what Keenan was talking about. He continued:
It is clear that when a station moves, the temperature data from before the move is not, in general, directly comparable to the data from after the move. This problem can occur even if the move is over a small distance. For example, if a station moves from being in the middle of a field to being by an asphalt area, then the measured temperatures would be expected to increase, even though the distance moved might be only 100 m. (A related issue is that the land use around a station can change over time, and this can affect measurements.)
In global warming studies, an important issue concerns the integrity of temperature measurements from meteorological stations. The latest assessment report from the IPCC indicates that the global average temperature rose by roughly 0.3 °C over the period 1954-1983. Thus, if errors in temperature measurements were of similar size to, or larger than, 0.3 °C, there could be a serious problem for global warming studies. The papers of Jones et al. and Wang et al. both consider this issue. The paper of Jones et al. is one of the main 2 works cited by the IPCC to support its contention that measurement errors arising from urbanization are tiny, and therefore are not a serious problem.
With that in mind, the problem Keenan identified was that the papers in question misrepresented the static condition of a large number of weather stations:
Regarding station movements over time, the papers of Jones et al. and Wang et al. make the following statements.
The stations were selected on the basis of station history: we chose those with few, if any, changes in instrumentation, location or observation times. [Jones et al.]
They were chosen based on station histories: selected stations have relatively few, if any, changes in instrumentation, location, or observation times.... [Wang et al.]
Unfortunately, these statements appear to be quite false:
Each paper gives the same reference for its statement: a report resulting from a project done jointly by the U.S. Department of Energy (DOE) and the Chinese Academy of Sciences (CAS). The DOE/CAS report (available via http://cdiac.esd.ornl.gov/ndps/ndp039.html) resulted from concern over “possible CO2-induced climate changes”. Its purpose was to present “the most comprehensive, long-term instrumental Chinese climate data presently available”. It contains, in particular, histories of some Chinese meteorological stations, including the different locations of those stations and the dates on which they moved, if any.
The DOE/CAS report was formally published in full in 1991-Wang et al. and Jones et al. used a pre-publication version of the report. A revised version of the report was published in 1997, but the station histories are the same in the two versions.
Jones et al. and Wang et al. consider the same 84 meteorological stations in China. Regarding 49 of those stations, the DOE/CAS report says, “station histories are not currently available” and “details regarding instrumentation, collection methods, changes in station location or observing times ... are not known” (sect. 5). For those 49 stations, then, the above-quoted statements from the two papers are impossible.
Shocking. But there was more:
Regarding the remaining 35 stations that were analyzed by the two papers, I have prepared a summary of the relevant information from the DOE/CAS report. The summary is available at http://www.informath.org/apprise/a5620/b17.htm. As an example from the summary, one station had five different locations during 1954-1983, with the locations as much as 41 km apart. Two other stations each had four different locations. At least half the stations had substantial moves (two other examples, of 25 km and 15 km, were given above). Moreover, several stations have histories that are inconsistent, making reliable analysis unattainable.
(The station that moved five times during the study period, #54511, is discussed by Yan et al. [Advances in Atmospheric Sciences, 18: 309 (2001)]; the authors conclude that some of the moves affected temperature measurements by 0.4 °C. The authors also discuss another station, #58367, which had a single move of 4 km; the authors conclude that the move affected temperature measurements by 0.3 °C. The authors’ statistical analysis, though, is invalid-e.g. it does not consider significance-so the conclusions are unproven.)
Additionally, the following statement from the DOE/CAS report seems apposite: “Few station records included in the PRC data sets can be considered truly homogeneous [i.e. have no significant changes in location, instrumentation, etc.]. Even the best stations were subject to minor relocations or changes in observing times, and many have undoubtedly experienced large increases in urbanization.”
The essential point here is that the quoted statements from Jones et al. and Wang et al. cannot be true and could not be in error by accident. The statements are fabricated.
For future reference, can I have a couple names and quotes?
If you want to believe that stations in Yemen and Sri Lanka are as well-maintained as US stations, go ahead, but unless a thorough review of station quality and temperature adjustment metrics is done, we cannot infer that global temp measurements are reliable to the precision required to say much about global warming. The potential signal to noise is too small.
You haven't read Peterson et al. on QA/QC of GHCN data, apparently.
I may reply more later. But the blogs are hashing this out pretty well, better than you or I could.
The process itself has been shown flawed and should be fixed.
Perhaps true. That does not, however, in any fashion, invalidate the current scientific understanding of anthropogenic global warming.
It cannot be fully self-checking if data and data adjustment methodology is not made transparent. Yes, they publish papers, but they don’t publish the underlying data that enable true reproducibility. This was part of the ‘hockey stick’ controversy as well. The climate science community has been overly lax in not making sure results are truly reproducible.
Perhaps true. That does not, however, in any fashion, invalidate the current scientific understanding of anthropogenic global warming.
Meteorological stations sometimes move, and this can affect the temperature measurements of the stations. For example, one of the stations relied upon by the above two papers was originally located on the upwind side of a city and later moved, 25 km, to be on the downwind side of the city. Such a move would be expected to increase the measured temperatures, because a city generates heat. Another station relied upon by the papers was originally located in the center of a city and then moved, 15 km, to be by the shore of a sea. Such a move would be expected to decrease the measured temperatures.
Apparently he didn't read Peterson et al. either.
And finally:
“Models indicate ...” models are not data.
The output from models IS data. If it wasn't, you couldn't check the validity of models against observations.