CRU and Gridcell 27.5N 117.5E

Yesterday, we had two curiosities from comparing GHCN data to HadCRU3 data – the apparent inconsistency between the HadCRU3 version in some gridcells e.g. 27.5N 117.5E and the apparent termination of much GHCN station data in 1990. Accordingly I collected all stations in the GHCN v2 data base from this gridcell and compared them with, as so often in climate science, surprising results in even the most mundane task.

In the GHCN data base, there were the following 20 stations in gridcell 27.5N 117.5E: CHANGTING, FUZHOU, GUANGCHANG, JIANYANG, JINGDEZHEN, JIUJIANG, JIUXIANSHAN, LISHUI, LONGYAN, LUSHAN, NANCHANG, NANCHENG, NANPING, PINGTAN, PUCHENG, QIXIANSHAN, QUXIAN, SHAOWU, TUNXI, YONG’AN.

Here is a re-plot of GHCN versions of the two Jones et al 1990 stations in this gridcell (Fuzhou, Nanchang) against the corresponding HadCRU3 gridcell. The HAdCRU3 values in the early 20th century are much colder than indicated by the Fuzhou station data or the few Nanchang measurements. There is also a substantial discontinuity between the periods for which the HadCRU3 series has values.

ghcnh57.gif ghcnh58.gif

In order to see whether this discontinuity was a result of one of the other stations, I plotted all 20 GHCN versions on one graph as shown below with the HadCRU3 version marked by black points. None of the 20 GHCN series had values that corresponded to the HadCRU3 version. The only station series that went into the early 20th century was the Fuzhou station (light grey here – already plotted above and which prompted the inquiry.) Fuzhou doesn’t go quite as early as the HadCRU3 gridcell version, so there’s still a mystery here as well.

At the recent end of the data, you’ll notice that only one series (magenta) emerges from the spaghetti graph. This is Nanchang – the other Jones et al 1990 station from this gridcell. Values for 19 out of 20 GHCN stations stop in 1990. I browsed other gridcells and the same pattern is very consistent: many gridcells will have many stations, but, in China, it appears that, for many gridcells, all but one station per gridcell stop in 1990. It is amazing when you see the data.

gridce98.gif
Plot of all GHCN v2 series in gridcell 27.5N, 117.5E

GHCN says that many station values are updated “irregularly”. I suspect that many people would have thought that an occasion would have arisen during any of the IPCC reports since the reign of Bush I that might have occasioned an update. Buy, hey, it’s climate science, and I guess that Phil Jones has been too busy, what with IPCC and all that, to actually update little details like Chinese station data.

In deference to Michael Mann’s worry about heavy lifting, inclusion of Chinese station information after 1990 will not require the transportation of heavy equipment like tree ring borers to “remote” locations.

If the Team is too busy to update the Chinese station data, dare one ask what the CRU contract with the U.S. Department of Energy contract actually requires them to do? 95% of the Chinese station data was collected by the U.S. itself ( see the TR055 program) nearly 20 years ago. What has the CRU been doing about Chinese data since then? Were they so convinced by Jones et al 1990 about Chinese UHI that they felt entitled to stop collecting information other than one big Chinese city for most gridcells? The Team never ceases to amaze.

There’s an obvious moral to this story. Ross McKitrick observed a long time ago that the Consumer Price Index is never be calculated by a bunch of academics at a university. It’s calculated by a proper statistical service who don’t mind doing little things like actually updating 95% of the Chinese data more frequently than once every 20 years. So aside from being surly and unresponsive with horrendous documentation of what they did, CRU doesn’t seem to be very efficient either. I wonder what justification the U.S. Department of Energy has for giving this inefficient program another cent.

And, not to be too distracted by CRU (and GHCN inefficiency), what of the adjustment that prompted the inquiry in the first place? There’s only one station in this gridcell that goes into the early 20th century Fuzhou – and its early 20th century values are relatively high. What is the explanation for the low values in the HadCRU3 gridcell? In other gridcells, I’ve been able to tie the HadCRU3 gridcell value to station values, but not here. Here we run into the CRU cone of silence: you have to quasi-litigate to try to get information on what stations were used in the gridcell; then you’d have to litigate to find out what they did and probably never really succeed. And by then, they’d have “moved on” and substituted some new and equally undocumented result.

Update:
here’s the NOAA gridded value for this gridcell compared with HAdCRU3. The Fuzhou values in the early part as well as the Nanchang values in the later part can be discerned in the NOAA gridcell. What did CRU do?

gridce3.gif

13 Comments

  1. Steve McIntyre
    Posted Apr 16, 2007 at 8:50 AM | Permalink | Reply

    Gou et 2007, cited by twq, refers to three Chinese stations: Maqin, Tongde and Xinhai, all said in Gou et al to have values up to 2001. However Tongde ends in 1990 at GHCN v2. Why? It’s not because the data doesn’t exist.
    So why hasn’t Tongde been updated at GHCN? What’s CRU been doing? Or GHCN for that matter?

    Maqin and Xinhai are not even in the GHCN v2 data base.

  2. Don Keiller
    Posted Apr 16, 2007 at 10:12 AM | Permalink | Reply

    Interesting stuff, Steve. By my eyeball, at least, there is not much evidence of HS-type profiles in this data either. Or maybe the HS emerges after the 1990s. Trouble is with the data as it stands, we just don’t know. I betcha, however, if it did show a HS-type profile, the Team would be shouting about it.

  3. EW
    Posted Apr 16, 2007 at 10:25 AM | Permalink | Reply

    As I read about the state of affairs in collecting and updating temperature data and more things about how the tree rings behave – is that really the state of evidence for global catastrophes based on which the whole world is expected to shill gazillions of whatever preferred currency?
    If THE decisive Earth temp is gauged from data of 3000 carefully worldwide selected meteostations (as the definition on one website says) and is so much more exact than anything concerning other troposphere measurements and if some of these data are in such a mess…

  4. Steve McIntyre
    Posted Apr 16, 2007 at 12:27 PM | Permalink | Reply

    I’ve posted up the corresponding series from NOAA gridded data, which is up to 3 deg C warmer than the HadCRU3 version in the early part of the 20th century for this gridcell. The HadCRU3 adjustment, whatever its justification, has the impact of enhancing the 20th century temperature increase. I wonder what CRU did.

  5. Don Keiller
    Posted Apr 16, 2007 at 1:01 PM | Permalink | Reply

    re#4 I suspect “Newspeak”, and and USSR “Pravda” could well have taken lessons in rewriting history from these guys. We are talking 3 degree “adjustments” here. I’ll try and suspend disbelief pending a detailed explanation of the rationale for this (and other) adjustments from CRU.

  6. Steve McIntyre
    Posted Apr 16, 2007 at 1:13 PM | Permalink | Reply

    I’ve sent the following inquiry to P Brohan of the Hadley Center:

    Enclosed are (1) a comparison of the HadCRU3 27.5N, 117.5E gridcell (red) against the corresponding NOAA gridcell (black), both in annualized form, showing a substantial difference prior to 1940; (2) a comparison of the same gridcell (shown here as black points) against all 20 GHCN v2 stations in the gridcell converted to annual anomaly format. Fuzhou is the light grey value in the early part of this series.

    I’ve consulted the publication Brohan et al 2006, but it sheds no light on the matter. Could you clarify what stations contributed to this gridcell calculation, whether the station versions used match the versions presently archived at GHCN v2 and what adjustments, if any, were carried out on the station data?

    Thanks for your attention, Steve McIntyre

  7. Steve McIntyre
    Posted Apr 16, 2007 at 1:18 PM | Permalink | Reply

    #5. Don, it will be fascinating to see what develops here. The adjustments always have a “good” reason, but it’s amazing how they all seem to go one way, isn’t it.

  8. Posted Apr 16, 2007 at 2:02 PM | Permalink | Reply

    #6

    Why not just preempt the inevitable refusal and ask him to consider your inquiry as being a request under the Freedom of Information Act/Environmental Information Act?

  9. twq
    Posted Apr 16, 2007 at 2:04 PM | Permalink | Reply

    I should post here.

    The below is a paper discussing the relationship between CRU data covering China and Chinese meteorological and historical data during the last 100 years. There is excellent agreement (0.84) between these annual two independent (before 1950) temperature series. 英国CRU 高分辨率格点资料æ?­ç¤ºçš„20 世纪中国气候å?˜åŒ– – æ¯?组 2 个 »
    闻新宇, 王ç»?武, 朱锦红 – 大气科学, 2006 – scholar.ilib.cn
    万方数�资�系统. 大气科学 CHINESE JOURNAL OF ATMOSPHERIC SCIENCES 2006

  10. esceptico
    Posted Apr 16, 2007 at 3:32 PM | Permalink | Reply

    An Overview of China Climate Change over the 20th Century Using UK UEA/CRU High Resolution Grid Data
    WEN Xin-Yu , WANG Shao-Wu , ZHU Jin-Hong, David VINER( 1 Department of Atmospheric Science, School of Physics, Peking University, Beijing 100871 ;2 Illinois State Water Survey, University of Illinois at Urbana-Champaign, Illinois, USA ; 3 Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, UK

    Abstract:

    The operational observations in China started in 1951. The availabity of instrumental observations is poor in the first half of the 20th century. Therefore, it is difficult to use them in discussing long term climate change issue. Although a number of proxy data could be used, the deficiencies are apparent, such as the coarse temporal and spatial resolution, etc. The University of East Anglia recently released the latest version of high resolution grid dataset, named as CRU-TS2.1. It is a completely covered monthly dataset of surface climatic variables. Compared with domestic observations, it has some merits concerning China climate change over the 20th century. Firstly, this dataset provides new information of the climate change over western China before 1950. Although it should be noted that the records are interpolated from observations, the results show significant correlation with the observation in the second half of the 20th century. Secondly, CRU dataset provides monthly mean fields, while domestic centuryscale series is just annual mean or seasonal mean data in the first half of the 20th century. Moreover, there are not any proxy data included in the construction of this dataset, which can bring noise and uncertainty. Hence, comparison between the CRU dataset and domestic observations is the way to verify the characteristics of China climate change during the 20th century and to validate the quality of the dataset in both China and UK. The results are as follows: (1) The interannual temperature variation is identical in both datasets. Their positive correlation coefficient is 0.84. They slightly differ from each other in the 1920s, when CRU underestimates the warming change in China, and therefore overestimates the warming trend of the whole century. (2) Even in the given 10 regional scales, both CRU and domestic data exhibit good consistency, apart from Tibet and Xinjiang areas. About one celsius degree bias is estimated by CRU in Tibet during the 1920s, which is the major difference from the reconstructed record. (3) The seasonal variability of precipitation over eastern China is identical in both series. The highest correlation coefficient (0.93) for 100 years among the four seasons is in autumn, while winter is the season that their correlation is the lowest one (0. 77). (4) CRU data exhibits appropriate interdecadal variation of temperature and precipitation as shown in China records. Particularly, CRU dataset also presents some primary features before 1951, especially in western China, where and when no observational data can be available. Therefore, CRU high resolution grid data present a more complete picture of climate change in China over the 20th century.

    Key words:China climate, the 20th century, high resolution, temperature, precipitation

  11. Steve McIntyre
    Posted Apr 16, 2007 at 3:45 PM | Permalink | Reply

    CRU TS2.1 appears to be a different data set than HadCRU3. (HadCRU3 is used in ICC AR4).

    The above article says:

    They slightly differ from each other in the 1920s, when CRU underestimates the warming change in China, and therefore overestimates the warming trend of the whole century.

    I guess these analyses are relevant to why CRU under-estimates Chinese warming in the early part of the century. One would expect that the CRU and Chinese temperature data would have a very high correlation since by and large they begin with the same data. A correlation of 0.84 is not very high under such circumstances and things like these CRU truncations and adjustments may explain why the correlation is not higher.

  12. Don Keiller
    Posted Apr 16, 2007 at 3:53 PM | Permalink | Reply

    re #10 I’m astonished at just how low some of these correlations are. Just how hard is it to read a thermometer?

  13. Hans Erren
    Posted Apr 16, 2007 at 4:15 PM | Permalink | Reply

    re 9:
    babelfish translates:

    The English CRU high resolution grid point material promulgates 20th century China climatic change – each group of 2 ‘–¡Wen Xinyu, Wang Shaowu, Zhu Jinhong – atmospheric sciences, 2006 – scholar.ilib.cn ten thousand sides data resources system Atmospheric sciences CHINESE JOURNAL OF ATMOSPHERIC SCIENCES 2006

2 Trackbacks

  1. By The End of CRUTEM? « Climate Audit on Jan 30, 2010 at 4:24 PM

    [...] in an April 2007 post here right after getting Chinese data from CRU from a (rare) successful FOI request. This post discussed [...]

  2. [...] receipt of the data, I did a number of posts at CA on the Chinese network e.g. here here here here here, analysis that we now know that Jones was monitoring. One of the few mentions of Climate Audit [...]

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