Climate Audit

KevinUK

Steve

This is excellent news. Well done for all you efforts which after 5 years looks as if they may be about to payoff. I think that once you’ve got the data you’ll see just how big a can of worms it all is. I’ll put good money on the fact that after you’ve sifted through it all and audited the Jones et al 1990 analysis that you’ll find that his claim of only 0.05C for UHI is bogus.

Slowly but surely you are getting there Steve. It hopefully won’t be too long now before you’ve completely pushed apart the pillars that are holding up the AGW temple. The high priests are going to be very happy but for the sake of real science you must do.

KevinUK

Dave Dardinger

Friday the 13th eh? Back luck perhaps, but for who is the question?

I’m still betting that the .05 deg C comes from taking the UHI from a selected set of towns / cities vs “rural” areas and then extrapolating to the entire world, rather than from determining what the amount of UHI is for each town in the grid and the correcting and extrapolating. I.e. if they’ve noticed a typical UHI would be 2 deg C for a city of 500,000+ they’ll then see what % of the surface is cities which have grown 500,000 in the past century and above and if it’s say, 2.5 % then they’ll come up with the .05 deg C. What they won’t have done is trying to correct their actual temperature measurement grid to allow for how much growth each of them has had. If, say, the average station has had a population growth in the area of 45,000 they won’t make an adjustment of .25 deg C if that’s what such growth would imply.

Bill F

So are they going to actually post the actual station data or just “annual temperature values” for them? It seems like the real devil is in the details, so if all they post is adjusted annual values, it would seem that the data would be of little use. Knowing the station names might allow you to download data from elsewhere, but that will probably be adjusted data, not the raw data Dr. Jones was working with.

John Hekman

Re: #7

Even if the data have been adjusted, if they only adjust 0.05 for the UHI, then the data should show a lot.

Willis Eschenbach

John L, when you say

The total adjustments to date by Hadley (Jones) and the GISS is about 0.7C as far as I can see.

which adjustments are you referring to?

w.

Douglas J. Keenan

The way that Steve’s request was initially processed seems wrong to me. Steve was told that his request would not be processed under the FOIAct, but under Environmental Information Regulations. As I read the statutes (IANL), the way things should have been handled is that (1) Steve’s FOIA request was formally refused and then (2) a separate request was made under the EIR. Formal refusal is always a significant action, for which there are rules that the Information Commissioner’s Office strongly enforces (apparently).

The university did not implement step 1 for Steve’s request, which appears to be incorrect procedure. When they tried to process my request the same way as Steve’s, I told them that if correct procedure was not followed, I would file a complaint with the ICO. For emphasis, I sent them a draft complaint letter.

Re #5, on the date. The date actually comes from the statute requiring that either the requested information is made available or the request is formally refused within 20 business days of the FOIA request being filed. My request was filed on March 12th; so the university has until April 11th to process it. Failure to do so would mean that I would be entitled to submit a violation-of-statute allegation to the ICO. That would be serious, and bad for the university. (Moreover, Palmer might end up being held responsible, even if it was not really his fault.) Palmer and I spoke cordially last week by telephone, and he was clearly wanting to meet the deadline.

Re #7, on station names. Jim Edwards had posted a comment observing that the station names that Steve was requesting were not “environmental information” as defined in the statutes. So by making my request for station names only, I was ensuring that it could not be validly processed under EIR.

I don’t know what the difference between EIR and FOIA statutes is with regard to making the information available (and Palmer told me that EIR can actually be stronger than FOIA). I thought that since Steve’s request was being processed under EIR, a second request should try something else. There is also a substantial difference in how the university processes refusals for the two. For refusals based on EIR, the university has an internal appeals procedure—which is what Steve was going through—whereas for refusals based on FOIA, appeals go directly to the ICO.

Jim Edwards

Is there anybody else who would’ve liked to have been a fly on the wall during an uncomfortable discussion between Dr. Jones talking about “those people”, “academic freedom”, and “I don’t have time for this” while Mr. Palmer explained the requirements of the law ?

Warwick Hughes

Re 16 John Lang and Willis,

Leaving aside Hansen for now, your Jones links refer to this variance adjustment process which I have always assumed, is carried out on gridded data. I am not aware of any significant changes in their “variance adjusted” grid cell trends compared to non VA trends but I’m open to being shown.

Moving now to station data where there has been an IPCC propaganda effort over a decade and a half to claim Jones et al data is adjusted for UHI. It is crystal clear from a reading of Jones et al 1986 documentation (the CDIAC books), reprinted in 1991, now out of print, that Jones et al adjustments were numero uno for inhomogeneities. A small proportion of UHI affected trends may have been caught in their homogeneity testing net but many more survived through to their gridded data.

As I have said before, the best way to grasp what Jones et al did is to read the 1988 critique by Wood and the Wigley & Jones reply, all scanned at: http://www.warwickhughes.com/cru86/wood.htm

W & J claimed Wood was in error on 9 points and I comment on these in a table. I have never seen a better source to understand what Jones et al have done than this 1988 exchange.

So John, where you say in 16 The adjustments made to the historical temperature records. Might it not be better to say, adjustments to gridded data ?

In respect of the Hadley Centre paper (Jones #5, tail end Charlie author), I believe much evidence points to the new HadCRUT3 dataset owing its birth to the unease of Hadley Centre mandarins at the quality of the daisy chain of Jones et al 1986, Jones 1994, Jones & Moberg 2003, various iterations of CRUT data. I address this in a blog post “Huge variations now between the 3 main global T datasets”: http://www.warwickhughes.com/blog/?p=82 and there is a web page linked with various global maps for 2005.

MarkR

If you want to get Lonnie Thompsons data, and all the others, a good lever would be a complaint to EPA under terms of OFFICE OF MANAGEMENT AND BUDGET
Guidelines for Ensuring and Maximizing the Quality, Objectivity, Utility, and Integrity of Information Disseminated by Federal Agencies; Republication Page 8460

10. Reproducibility” means that the information is capable of being substantially reproduced, subject to an acceptable degree of imprecision. For information judged to have more (less) important impacts, the degree of imprecision that is tolerated is reduced (increased). If agencies apply the reproducibility test to specific types of original or supporting data, the associated guidelines shall provide relevant definitions of reproducibility (e.g., standards for replication of laboratory data). With respect to analytic results, capable of being substantially reproduced” means that independent analysis of the original or supporting data using identical methods would generate similar analytic results, subject to an acceptable degree of imprecision or error.

3. To facilitate public review, agencies shall establish administrative mechanisms allowing affected persons to seek and obtain, where appropriate, timely correction of information maintained and disseminated by the agency that does not comply with OMB or agency guidelines. These administrative mechanisms shall be flexible, appropriate to the nature and timeliness of the disseminated information, and incorporated into agency information resources management and administrative practices.
i. Agencies shall specify appropriate time periods for agency decisions on whether and how to correct the information, and agencies shall notify the affected persons of the corrections made.
ii. If the person who requested the correction does not agree with the agency’s decision (including the corrective action, if any), the person may file for reconsideration within the agency. The agency shall establish an administrative appeal process to review the agency’s initial decision, and specify appropriate time limits in which to resolve such requests for reconsideration.

Page 8459

Both the Fig 1 and Fig 2 are based on data which is not available as it should be under the terms of the US Federal Guidelines.

Also the Fig 1 fails the objectivity test, as it does not fairly state that atmospheric CO2 levels rise after temperature increases, and not before them, and fall after temperature falls not before them.

Objectivity” focuses on whether the disseminated information is being presented in an accurate, clear, complete, and unbiased manner, and as a matter of substance, is accurate, reliable, and unbiased.

Page 8453

If they didn’t correct the information, they would have to take the graphics and text off the EPA web site.

All it would take is a US citizen and a letter or email.

Steve Sadlov

RE: #20 – Here’s my attempted posted, en queue, at that thread:

===============

RE: #221 – With notable exceptions due to peat compaction (Delta) and ground water mining induced local subsidence (Alviso) the main problem, historically, has tended to actually be maintainence of navigability. The combination of siltation and tectonic emergence has tended to continuously push the low tide line versus fixed geodetic reference points in an offshore / estuary mouth direction. I would be curious to see if, assuming it is consistent, global rise of MSL would counter these trends, or even significantly slow them.
by Steve Sadlov

===============

Tim Ball

It appears East Anglia and Hadley are distancing themselves from Jones as the probing continues.

Tim Ball

#24
East Anglia appears to have realized, thanks to Steve M and other requests for information, that their reputation is being sullied. Regardless of the type of data, common sense and common practice almost everywhere else would indicate access to data to pursue the scientific method is not only reasonable but necessary. Why else would we have such a focus on freedom of information – rhetorical answer to a rhetorical question, because the devil’s work is done in the darkness.
I also read that Hadley had put new people in charge of the data processing, which suggest to me they also are aware of and don’t need unnecessary controversy. Whatever else they may be bureaucrats are extremely aware of the bright light of controversy and the unwanted attention it can bring.

Steve McIntyre

#26. First of all, please recognize that it’s quite possible that their data is perfectly in order and they are being obstreperous just because they can. I would say that there’s a distinct possibility, perhaps even probability of this.

Second, the purpose of an audit is not necessarily to find fault, but to provide confidence to people relying on the data. I don’t necessarily think that there’s a big deal in this particular data set; but equally, it shouldn’t be secret.

Third, it’s very difficult to audit things without cooperation from the host. In this particular case, given the attitude of the host, there’s little guarantee that all the relevant information will be provided.

Jean S

I suppose the promised data is available here:
http://www.cru.uea.ac.uk/cru/data/jonesetal1990/

Steve McIntyre

I suspect that there are a number of people that might be interested in wading through various stations. The blog format has such a flood of posts that it’s hard to keep track of. A wiki format would probably be better for that – in which there would be an entry for each station.

I notice that Jones didn’t post up which were in the rural and which were in the urban network or provide names for the Chinese stations. There were 3 wmo numbers in the J90 list that had no match in the 65+205 wmo numbers:
id wmo lat latm long longm
41 8 52983 35 35 103 11
45 4 53161 43 54 125 20
62 13 55606 28 36 115 58

Here are identifications for 81 sites within the 65+205.

id wmo lat latm long longm name
1 4 50854 46 23 125 19 Anda
2 3 50949 45 7 124 50 Qian Gorlos
3 3 54135 43 36 122 16 Tongliao
4 7 54497 40 3 124 20 Dandong
5 4 50963 45 58 128 44 Tonghe
6 7 54324 41 33 120 27 Chaoyang
7 4 50756 47 26 126 58 Hailun
8 7 54616 38 20 116 50 Cangzhou
9 7 54725 37 30 117 32 Huimin
10 7 54476 40 10 122 9 Gaixian Xiongyue
11 10 54936 35 35 118 50 Juxian
12 10 54852 36 56 120 42 Laiyang
13 10 54916 35 34 116 51 Yanzhou
14 9 57193 33 47 114 31 Xihua
15 12 57378 31 10 112 34 Zhongxiang
16 12 57584 29 23 113 5 Yueyang
17 12 57662 29 3 111 41 Changde
18 10 58144 33 36 119 2 QingJiang
19 10 58150 33 46 120 15 Sheyang
20 15 57799 27 7 114 58 Jian
21 13 58314 31 24 116 19 Huoshan
22 10 58251 32 51 120 19 Dongtai
23 16 58754 27 20 120 12 Fuding
24 15 59293 23 44 114 41 Heyuan
25 15 59417 22 22 106 45 Longzhou
26 13 58477 30 2 122 7 Dinghai
27 13 58646 28 27 119 55 Li Shui
28 16 59501 22 47 115 22 Haifen Shanwei
29 12 57537 29 18 108 10 Pengshui
30 12 57606 28 8 105 50 Tongzi
31 11 56287 29 59 103 0 Yaan
32 14 56751 25 42 100 11 Dali
33 9 57253 33 51 110 49 Yunxian
34 12 57504 29 35 105 3 Neijiang
35 11 56193 32 25 104 31 Pingwu
36 9 57127 33 4 107 12 HanZhong
37 9 53863 37 30 111 56 Jiexiu
38 8 53915 35 33 106 40 Pingliang
39 1 51379 44 1 89 34 Qitai
40 6 53593 39 50 114 34 Weixian
41 8 52983 35 35 103 11
42 6 53336 41 34 108 31 Urad Zhongqi
43 3 50745 47 23 123 55 QiQiHaEr
44 4 50953 45 41 126 37 HaErBin
45 4 53161 43 54 125 20
46 7 54342 41 46 123 26 ShenYang
47 4 50978 45 17 130 57 Jixi
48 7 54237 42 2 121 39 Fuxin
49 4 50774 47 43 128 54 Yichun
50 7 54511 39 56 116 17 BeiJing
51 7 54527 39 6 117 10 TianJin
52 7 54662 38 54 121 38 DaLian
53 10 54823 36 41 116 59 JiNan
54 10 54857 36 4 120 20 QingDao
55 9 57083 34 43 113 39 ZhengZhou
56 9 57073 34 40 112 25 Luoyang
57 12 57461 30 42 111 18 YiChang
58 12 57494 30 37 114 8 WuHan
59 12 57679 28 12 113 5 ChangSha
60 10 58027 34 17 117 9 XuZhou
61 13 58238 32 3 118 47 NanJing
62 13 55606 28 36 115 58
63 13 58321 31 52 117 14 Hefei
64 13 58367 31 10 121 26 ShangHai
65 16 58847 26 5 119 17 FuZhou
66 15 59287 23 8 113 19 GuangZhou
67 15 59431 22 49 108 21 NanNing
68 13 58457 30 14 120 10 HangZhou
69 13 58659 28 1 120 40 WenZhou
70 16 59316 23 24 116 41 ShanTou
71 12 57516 29 35 106 28 ChongQing
72 15 57816 26 35 106 43 GuiYang
73 11 56294 30 40 104 1 ChengDu
74 14 56778 25 1 102 41 KunMing
75 12 57447 30 17 109 28 Enshi
76 11 56386 29 34 103 45 Leshan
77 11 56196 31 28 104 41 Mianyang
78 9 57036 34 18 108 56 XiAn
79 6 53772 37 47 112 33 TaiYuan
80 8 52889 36 3 103 53 LanZhou
81 1 51463 43 47 87 37 WuLuMuQi
82 6 53487 40 6 113 20 Datong
83 8 52866 36 37 101 46 XiNing
84 6 53463 40 48 111 38 HuHeHaoTe

Bishop Hill

#31, #32

Everything from approx no 44 onwards look like big cities to me – mostly provincial capitals.

John A

Steve McIntyre:

I suspect that there are a number of people that might be interested in wading through various stations. The blog format has such a flood of posts that it’s hard to keep track of. A wiki format would probably be better for that – in which there would be an entry for each station.

Is that a request?

Steve McIntyre

Thanks for observing that the webpage gives info on the ordering of the stations as follows:

“The ordering of the data for the Chinese stations gives the urban sites first, then the rural, so opposite to the order with the locations”.

Now this is from the Team so you have to be a bit careful, especially when they don’t identify the cities. The above sentence means: in the list of locations, the rural sites are listed first; in the data files, the urban sites are listed first. The sentence is correct but hard to understand. Here’s a plot of the locations in the new file – red: rural; black -urban.

In the western China area near Dulan (38N, 102E) that we’ve been discussing in connection with Dulan junipers, the two urban sites are Lanzhou and Xining; the rural sites are Pingliang and unidentified 53983, both south of 36N.

Steve Sadlov

Na Ning has incurred a growth explosion (above and beyond that of major places like Shang Hai, Guang Zhou, etc) since 1980. The major metros themselves have expanded both outward and upward. Take Guang Zhou. For centuries, it was an established megaregional capital (in fact, one of the oldest cities in China). There was a spurt of heavy industrialization from 1920 – the Cultural Revolution. Then, once the CR ended, it became a preferred place for Hong Kongers, and outright foreigners, to set up low cost operations. This predates the better known Shen Zhen developments. For a short while, it seemed Shen Zhen would eclipse Guang Zhou. But more recently, Guang Zhou took off with second wind. The ring of quasi rural places, like Shun De, Dong Guan, etc … have become de facto exurbs or even suburbs. Not to long from now, there will be a continous connurbation along both sides of the Pearl River estuary, Stretching from Macao, through its apex at Guang Zhou and ending at Hong Kong if not further to the ENE along the coast.

Willis Eschenbach

Well, my struggle with the FOI and Jones goes on … here’s the latest:

Dear Mr. Eschenbach

FREEDOM OF INFORMATION ACT 2000 – INFORMATION REQUEST
(FOI_07-04)

In your email of 8 March 2007, you stated that you wished to see

“1) A list of the actual sites used by Dr. Jones in the preparation of the HadCRUT3 dataset, and
2) A clear indication of where the data for each site is available. This is quite important, as there are significant differences between the versions of each site’s data at e.g. GHCN and NCAR.”

As part of our obligation to, at first instance, try to resolve appeals informally, I have been in discussion with the relevant members of UEA and can offer the following further explanation of our response to your original request.

In regards the ‘gridded network’ stations, I have been informed that the Climate Research Unit’s (CRU) monthly mean surface temperature dataset has been constructed principally from data available on the two websites identified in my letter of 12 March 2007. Our estimate is that more than 98% of the CRU data are on these sites.

The remaining 2% of data that is not in the websites consists of data CRU has collected from National Met Services (NMSs) in many countries of the world. In gaining access to these NMS data, we have signed agreements with many NMSs not to pass on the raw station data, but the NMSs concerned are happy for us to use the data in our gridding, and these station data are included in our gridded products, which are available from the CRU web site. These NMS-supplied data may only form a very small percentage of the database, but we have to respect their wishes and therefore this information would be exempt from disclosure under FOIA pursuant to s.41. The World Meteorological Organization has a list of all NMSs.

We hope that that this information satisfies your request and that it will resolve this matter amicably and to your satisfaction.

If you are dissatisfied with the handling of your complaint please contact me at:
University of East Anglia
Norwich
NR4 7TJ
Telephone: 0160 359 3523
E-mail: foi@uea.ac.uk

If you are dissatisfied with the final adjudication of your complaint by our internal complaint process, you have the right of appeal to the Information Commissioner at:
Information Commissioner’s Office
Wycliffe House
Water Lane
Wilmslow
Cheshire
SK9 5AF
Telephone: 01625 545 700
Website: http://www.ico.gov.uk

Yours sincerely

David Palmer
Information Policy Officer
University of East Anglia

I will persevere.

w.

Steve McIntyre

Here’s a reconciliation of Jones data. Three id’s appear to be incorrect:
(52984,54161,58606) replace #52983, 53161, 55606
one latitude is incorrect (I use these to locate GHCN id id no match)-Yunxian is 32.85 not 33.85
The sites are matched initially to the sites in the CDIAC China archive. Then GHCN id’s are located (which require id’s not just wmo ids.) The population and population codes are from GHCN v2 http://www1.ncdc.noaa.gov/pub/data/ghcn/v2/v2.temperature.inv. ipop codes are R-rural, S -small city; U – urban. So a number of J90 “rural” sites wer classified by GHCN as urban or small city. A reader has sent me some recent populations and I will update that after some QC.

wmo lat long name pop ipop ghcn
1 1 50854 46.38333 125.31667 Anda 110 U 50854000
2 2 50949 45.11667 124.83333 Qian Gorlos -9 R 50949000
3 3 54135 43.60000 122.26667 Tongliao 80 U 54135000
4 4 54497 40.05000 124.33333 Dandong 450 U 54497000
5 5 50963 45.96667 128.73333 Tonghe 20 S 50963000
6 6 54324 41.55000 120.45000 Chaoyang 60 U 54324000
7 7 50756 47.43333 126.96667 Hailun 75 U 50756000
8 8 54616 38.33333 116.83333 Cangzhou 100 U 54616000
9 9 54725 37.50000 117.53333 Huimin 20 S 54725000
10 10 54476 40.16667 122.15000 Gaixian Xiongyue -9 R 54471001
11 11 54936 35.58333 118.83333 Juxian 30 S 54945001
12 12 54852 36.93333 120.70000 Laiyang 30 S 54863001
13 13 54916 35.56667 116.85000 Yanzhou 100 U 54916000
14 14 57193 33.78333 114.51667 Xihua -9 R 57193000
15 15 57378 31.16667 112.56667 Zhongxiang 45 S 57378000
16 16 57584 29.38333 113.08333 Yueyang -9 R 57584000
17 17 57662 29.05000 111.68333 Changde -9 R 57662000
18 18 58144 33.60000 119.03333 QingJiang 110 U 58144000
19 19 58150 33.76667 120.25000 Sheyang -9 R 58150000
20 20 57799 27.11667 114.96667 Jian 100 U 57799000
21 21 58314 31.40000 116.31667 Huoshan -9 R 58314000
22 22 58251 32.85000 120.31667 Dongtai 40 S 58251000
23 23 58754 27.33333 120.20000 Fuding 25 S 58754000
24 24 59293 23.73333 114.68333 Heyuan 25 S 59293000
25 25 59417 22.36667 106.75000 Longzhou -9 R 59417000
26 26 58477 30.03333 122.11667 Dinghai 37 S 58477000
27 27 58646 28.45000 119.91667 Li Shui -9 R 58646000
28 28 59501 22.78333 115.36667 Haifen Shanwei -9 R 59501000
29 29 57537 29.30000 108.16667 Pengshui 27 S 57633001
30 30 57606 28.13333 105.83333 Tongzi -9 R 57602001
31 31 56287 29.98333 103.00000 Yaan -9 R 56287000
32 32 56751 25.70000 100.18333 Dali -9 R 56751000
33 33 57253 32.85000 110.81667 Yunxian 30 S 57259001
34 34 57504 29.58333 105.05000 Neijiang 240 U 57504000
35 35 56193 32.41667 104.51667 Pingwu -9 R 56193000
36 36 57127 33.06667 107.20000 HanZhong 120 U 57127000
37 37 53863 37.50000 111.93333 Jiexiu -9 R 53863000
38 38 53915 35.55000 106.66667 Pingliang 85 U 53915000
39 39 51379 44.01667 89.56667 Qitai 70 U 51379000
40 40 53593 39.83333 114.56667 Weixian -9 R 53593000
41 41 52984 35.58333 103.18333 Linxia 100 U 56080002
42 42 53336 41.56667 108.51667 Urad Zhongqi -9 R 53336000
43 43 50745 47.38333 123.91667 QiQiHaEr 1500 U 50745000
44 44 50953 45.68333 126.61667 HaErBin 2750 U 50953000
45 45 54161 43.90000 125.33333 ChangChun 1500 U 54161000
46 46 54342 41.76667 123.43333 ShenYang 3750 U 54342000
47 47 50978 45.28333 130.95000 Jixi 350 U 50978000
48 48 54237 42.03333 121.65000 Fuxin 350 U 54236001
49 49 50774 47.71667 128.90000 Yichun 200 U 50774000
50 50 54511 39.93333 116.28333 BeiJing 8500 U 54511000
51 51 54527 39.10000 117.16667 TianJin 7210 U 54527000
52 52 54662 38.90000 121.63333 DaLian 1480 U 54662000
53 53 54823 36.68333 116.98333 JiNan 1500 U 54823000
54 54 54857 36.06667 120.33333 QingDao 1900 U 54857000
55 55 57083 34.71667 113.65000 ZhengZhou 1500 U 57083000
56 56 57073 34.66667 112.41667 Luoyang 750 U 57071001
57 57 57461 30.70000 111.30000 YiChang 150 U 57461000
58 58 57494 30.61667 114.13333 WuHan 4250 U 57494000
59 59 57679 28.20000 113.08333 ChangSha 850 U 57679000
60 60 58027 34.28333 117.15000 XuZhou 1500 U 58027000
61 61 58238 32.05000 118.78333 NanJing 2000 U 58238000
62 62 58606 28.60000 115.96667 NanChang 900 U 58606000
63 63 58321 31.86667 117.23333 Hefei 400 U 58321000
64 64 58367 31.16667 121.43333 ShangHai 10980 U 58362000
65 65 58847 26.08333 119.28333 FuZhou 900 U 58847000
66 66 59287 23.13333 113.31667 GuangZhou 2300 U 59287000
67 67 59431 22.81667 108.35000 NanNing 375 U 59431000
68 68 58457 30.23333 120.16667 HangZhou 1100 U 58457000
69 69 58659 28.01667 120.66667 WenZhou 250 U 58659000
70 70 59316 23.40000 116.68333 ShanTou 400 U 59316000
71 71 57516 29.58333 106.46667 ChongQing 3500 U 57516000
72 72 57816 26.58333 106.71667 GuiYang 1500 U 57816000
73 73 56294 30.66667 104.01667 ChengDu 2000 U 56294000
74 74 56778 25.01667 102.68333 KunMing 1300 U 56778000
75 75 57447 30.28333 109.46667 Enshi 40 S 57447000
76 76 56386 29.56667 103.75000 Leshan 250 U 56385001
77 77 56196 31.46667 104.68333 Mianyang 52 U 56196000
78 78 57036 34.30000 108.93333 XiAn 1900 U 57036000
79 79 53772 37.78333 112.55000 TaiYuan 2725 U 53772000
80 80 52889 36.05000 103.88333 LanZhou 1500 U 52889000
81 81 51463 43.78333 87.61667 WuLuMuQi 500 U 51463000
82 82 53487 40.10000 113.33333 Datong 300 U 53487000
83 83 52866 36.61667 101.76667 XiNing 250 U 52866000
84 84 53463 40.80000 111.63333 HuHeHaoTe 700 U 53463001

Hans Erren

Jan Lahmeyer has this data:

CHINA
historical demographical data of the urban centers

http://populstat.info/Asia/chinat.htm

Steve Sadlov

RE: #47 – Even classically rural areas including ones far removed from urban centers have changed dramatically since the early 20th century particularly since the efforts around rural electrification and infrastructure development commenced. In the US, this started during the 1930s – in other parts of the world, later (in some cases much later, as in, since 1980). A change from quasi homesteading and subsitance farming (replete with extreme poverty and low per capita energy dissipiation) to modern scientific agriculture (not to mention examples of “urban escape” industry, typically for cost reasons) brings with it changes in land use, the distribution and gross amount of energy dissipation, not to mention albedo modification. Add on top of that the impacts of the many and growing recreation oriented developments aimed at increasingly affluent and mobile urbanites, and we end up with a “rural” environment whose energetics approach those of the most typical suburban environments of the middle 20th century. Here in California, there is nearly continuous suburban strip style development along the main roads spanning from the suburbs of San Francisco proper, almost all the way to Yosemite National Park.

Willis Eschenbach

Thanks, Earle. First I have to get the station information, so I can tell which NMSs to target … grrrrr.

w.

Willis Eschenbach

Well, I have replied to Mr. Palmer’s response to my FOI request, as follows:

Dear Mr. Palmer:

Thank you for your response. However, it does not solve the problem. In your original response you said:

Your request for information received on 28 September now been considered and I can report that the information requested is available on non-UEA websites as detailed below.

The Global Historical Climatology Network (GHCN-Monthly) page within US National Climate Data Centre website provides one of the two US versions of the global dataset and includes raw station data. This site is at:
http://www.ncdc.noaa.gov/oa/climate/ghcn-monthly/index.php

This page is where you can get one of the two US versions of the global dataset, and it appears that the raw station data can be obtained from this site.

Datasets named ds564.0 and ds570.0 can be found at The Climate & Global Dynamics Division (CGD) page of the Earth and Sun Systems Laboratory (ESSL) at the National Center for Atmospheric Research (NCAR) site at: http://www.cgd.ucar.edu/cas/tn404/

Between them, these two datasets have the data which the UEA Climate Research Unit (CRU) uses to derive the HadCRUT3 analysis. The latter, NCAR site holds the raw station data (including temperature, but other variables as well). The GHCN would give their set of station data (with adjustments for all the numerous problems).

They both have a lot more data than the CRU have (in simple station number counts), but the extra are almost entirely within the USA. We have sent all our data to GHCN, so they do, in fact, possess all our data.

In accordance with S. 17 of the Freedom of Information Act 2000 this letter acts as a Refusal Notice, and the reasons for exemption are as stated below

Exemption Reason

s. 21, Information accessible to applicant via other means Some information is publicly available on external websites

While it is good to know that the data is available at those two web sites, that information is useless without a list of stations used by Jones et al. to prepare the HadCRUT3 dataset. As I said in my request, I am asking for:

1) A list of the actual sites used by Dr. Jones in the preparation of the HadCRUT3 dataset, and

2) A clear indication of where the data for each site is available. This is quite important, as there are significant differences between the versions of each site’s data at e.g. GHCN and NCAR.”

Without knowing the name and WMO number of each site and the location of the source data (NCAR, GHCN, or National Met Service), it is not possible to access the information. Thus, Exemption 21 does not apply – I still cannot access the data.

I don’t understand why this is so hard. All I am asking for is a simple list of the sites and where each site’s data is located. Pointing at two huge piles of data and saying, in effect, “The data is in there somewhere” does not help at all.

To clarify what I am requesting, I am only asking for a list of the stations used in HadCRUT3, a list that would look like this:

WMO#_____Name_____Source
58457____HangZhou___NCAR
58659____WenZhou____NCAR
59316____ShanTou____GHCN
57516____ChongQing___NMS

etc. for all of the stations used to prepare the HadCRUT3 temperature data.

That is the information requested, and it is not available “on non-UEA websites”, or anywhere else that I have been able to find.

I appreciate all of your assistance in this matter, and I trust we can get it resolved satisfactorily.

Best regards,

w.

The beat goes on … as the I Ching says … “Perseverance furthers.”

w.

MarkW

Was that freedom OF information, or freedom FROM information?

mark

Re #55: Good luck, keep the pressure up