Climate Audit

Steve McIntyre

#1. Thanks. I’ve input that data into my spread sheet and re-uploaded it. There are definitely some small population sites in the list, which is good.

Brooks Hurd

Steve,

These stations are located in eastern China where the world’s highest rate of urban growth has occured over the past century. The rate has accellerated since Mao’s death. People say that if you only go to China once a year, that you will not recognize it. This is not far from the truth.

When I was in Shanghai in September and October last year, it was my first trip since 1998. The city had expanded in 3 dimensions to such an extent that it was mind boggling. In 1998 the population estimate was 12 million people. Today, I heard estimates ranging from 15 to 19 million inhabitants. I believe that the actual population is closer to the high end than to the low end of these estimates. Any census badly underestimates populations by the time it is published.

By selecting stations in eastern China, I am certain that Jones has built into his data a large amount of urban growth. Jones’ claim that the station data is homogeneous flies in the face of the reality of growth in eastern China.

John Hekman

I think what is needed is to take a statistically valid sample of temp stations and do an in-depth and site-visit analysis of them to see if they can be relied on to measure 100 years of temp history. Roy Spenser did something like this in his article about the California Central Valley and the effects of land use on temp measurements.

nanny_govt_sucks

Selecting Russia and China as areas with homogenous temperature records just repeats a theme of a kind of distain for all things American or at least Western. Jones appears to be unable to resist slapping the West in the face with another veiled bogus charge. It’s the horrid emissions, or the depraved record keeping – take your pick – that makes the West “evil”, in Jones’ eyes anyway. Only the Communists can do this stuff right.

Steve Sadlov

In general the sites are within the most heavily populated part of China with very few out in the desolate Western areas. Even in “rural” parts of the East, development patterns and population density would qualify as low income suburban by Western standards. In that part of the country, you are never far away from other people. Even in farming areas, the properties are 10s of an acre or less, sometimes much less, with a home (at least one home) on each plot. Very small scale farming is the norm in Eastern China. And industry is scattered throughout.

Steve Sadlov

RE: #5 – And nearby Shanghai, in a so called “rural” area, look at what has happened with Kun Shan since the early 1990s! That is but one specific example.

pj

Steve,

You are doing great work on this site. The surface record has bothered me for a number of years, though I haven’t had the wherewithal
to look into it in great depth. This kind of work has been sorely needed within the climate science community. It’s really a shame
that it has to come from without. Keep it up.

MarkW

In other words, unless someone can prove that the data is bad, Jones accepts it as good.

Steve McIntyre

#18. There’s a big difference between malfeasance and bias. Authors proposing that past temperatures be reduced justify this in terms of time-of-observation bias and they can support these arguments. The difficulty arises because the amount of the adjustment seems to be about the same size as the effect being measured. I get the impression that the authors are much more zealous in finding reasons to adjust past temperatures than the opposite and are too quick to accept very slight and weakly argued papers arguing against (say) UHI. I don’t think that it’s helpful to worry about malfeasance. This doesn’t appear to be a case where authors are withholding adverse verification statistics.

Louis Hissink

#20 – bit of an internet wizzle – the first sentence is missing anomaly ” ..that adjustment for level makes a geochemical ANOMALY disappear…”.

🙂

JP

Means and standard deviations of each station’s respective monthly values were calculated. Values lying 3.5 or more standard deviations away from their respective means were flagged if not corroborated by temperatures at neighboring stations

I understand perfectly why the temp, precip, cloud cover, and other quantifiable data would under go standard deviation
checks, but weather conditions unlike some other types of data can have fluccuations due to geography. If they applied this procedures in Central Europe they could have big problems. Cloud cover and or fog due can keep one station in a “cold regime” relative to its adjacent stations for days on end. I’ve seen in Germany where a small drainage wind can clear stratiform clouds from one valley, while the next valley 3km away remains in 0/0 conditions. Even in the Great Plains, where the terrain in fairly even, snow cover can affect surface temperatures and cloud cover. I wonder if researchers appply thier QA checks with a intimate understanding of the local geography and all of its attendent quirks. By smoothing the instrument readings to this degree, the researchers are creating a climate picture that in the long run doesn’t exist.

On the other hand, the data validation subroutines built into the short range forecast models for NOAA and the Air Force concentrate on obvious errors (wind gusts to 500mph, hour to hour temp increases over over 15 deg F, etc..) the observations are kicked back to the observer for correction or validation; if the station is automated and had preceived errors, the readings in question were given a reality check.

pat

I found this on Michael Crichton’s website from his 2005 testimony to the US Senate.

For a person with a medical background, accustomed to this degree of rigor in research, the protocols of climate science appear considerably more relaxed. In climate science, it’s permissible for raw data to be “touched,” or modified, by many hands. Gaps in temperature and proxy records are filled in. Suspect values are deleted because a scientist deems them erroneous. A researcher may elect to use parts of existing records, ignoring other parts. But the fact that the data has been modified in so many ways inevitably raises the question of whether the results of a given study are wholly or partially caused by the modifications themselves.

http://www.michaelcrichton.net/speeches/index.html

The “relaxed” approach to data handling seems to be in evidence here.

Warwick Hughes

I have just put up a page on the Jones et al 1990 Eastern China region showing what can be readily learned about the identity of their 42 urban / rural station pairs.
http://www.warwickhughes.com/papers/echina42.htm

Steve Sadlov

RE: #27 – A number of them outside of China, especially quite a cluster in Bangladesh. Two on Taiwan, one right at Keelung (major port which started its boom after WW2) and another just south of the high tech mecca of Hsin Chu (a post 1970s development). Quite a cluster in the part of Japan which is visible, we all know what has happened to the “rural” areas of Soutwestern Japan since the 1950s (massive growth in industry and the residential developments to accomodate all its people).

UC

#30

Brohan et al:

The studies finding a large urbanisation effect [Kalnay & Cai, 2003, Zhou et al., 2004] are based on comparison of observations with reanalyses, and assume that any difference is entirely due to biases in the observations. A comparison of HadCRUT data with the ERA- 40 reanalysis [Simmons et al., 2004] demonstrated that there were sizable biases in the reanalysis, so this assumption cannot be made, and the most reliable way to investigate possible urbanisation biases is to compare rural and urban station series.

Zhou et al:

It is impossible to find a corresponding rural station for most of the urban ones, especially in eastern and southern China. Consequently, if using the rural’€”urban difference to estimate the UHI, one possibly is comparing temperature between two different urban stations at regional scales or between two different regions at large scales.

Jones 90:

We assembled a network of 42 station pairs of rural and urban sites in the eastern half of China.

They should just give up and admit that ‘we know nothing’..

Simmons 2004 : Simmons, A. J., P. D. Jones, V. da Costa Bechtold, A. C. M. Beljaars, P. W. Kà¥llberg, S. Saarinen, S. M. Uppala, P. Viterbo, and N. Wedi (2004), Comparison of trends and low-frequency variability in CRU, ERA-40, and NCEP/NCAR analyses of surface air temperature , J. Geophys. Res., 109, D24115, doi:10.1029/2004JD005306.