Climate Research Unit hacked, damning evidence of data manipulation

[LunarRay]

None of this really matters in the end. We will know in 50-70 years time or not. Let's say anthropomorphic global warming is real. It's not like the global economies will ever agree on the kind of steps really necessary to prevent a disaster. And if it isn't real well then we will have egg on our faces. Either way it's largely a wait and see game. The global warming deniers will never be swayed anyway.

I think that some aspects of 'going green' are good regardless of which way our climate is going. We do breathe and in big cities the air is hard to chew.

I think I'm more prone to accept what I know little about by looking at what I know a bit more about. We can stimulate the economy or we can follow the other nations who think going green at home and more or less forcing the US will give them market share in the US. I don't for a moment think China would go green but for some economic advantage they might get by agreement with the Warming Notion. IF the US lags in development and implementation we'll miss out on the opportunity to transition from Fossil to Green as the leader and major producer of green stuff.

 

[IGBT]

None of this really matters in the end. We will know in 50-70 years time or not. Let's say anthropomorphic global warming is real. It's not like the global economies will ever agree on the kind of steps really necessary to prevent a disaster. And if it isn't real well then we will have egg on our faces. Either way it's largely a wait and see game. The global warming deniers will never be swayed anyway.

and the eco-KOOKS will always gravitate towards some variant of eco-alarmism. now that the cover has been blown off their climate hoax I'll bet they already have some new alarmist scam ready to hatch.

 

[Locut0s]

and the eco-KOOKS will always gravitate towards some variant of eco-alarmism. now that the cover has been blown off their climate hoax I'll bet they already have some new alarmist scam ready to hatch.

Like I said we'll see in 60 years time or so.

 

[Ozoned]

Like I said we'll see in 60 years time or so.

The changes will be so gradual that most won't even notice them.

 

[Fear No Evil]

The changes will be so gradual that most won't even notice them.

What? You haven't seen the movies? It will end with 200 foot tidal waves in NYC.

 

[brencat]

None of this really matters in the end. We will know in 50-70 years time or not. Let's say anthropomorphic global warming is real. It's not like the global economies will ever agree on the kind of steps really necessary to prevent a disaster. And if it isn't real well then we will have egg on our faces. Either way it's largely a wait and see game. The global warming deniers will never be swayed anyway.

Sorry, but I'm not willing to risk American hegemony or economic dominance in the world and have the outcome be that global warming wasn't real. If we don't have irrefutable proof and emerging economies won't contribute to a CO2 cutback, then this issue should be tabled indefinitely. Let the chips fall where they may. Sounds harsh, cruel, and neanderthalish right? Good. Go cry on a shoulder that cares...

But with the release of these emails and data, there's definitely some suspicious book-cooking going on. All the more reason to take our time with policies that will make us all poorer, raise energy costs, and drive jobs away.

 

[sandorski]

Sorry, but I'm not willing to risk American hegemony or economic dominance in the world and have the outcome be that global warming wasn't real. If we don't have irrefutable proof and emerging economies won't contribute to a CO2 cutback, then this issue should be tabled indefinitely. Let the chips fall where they may. Sounds harsh, cruel, and neanderthalish right? Good. Go cry on a shoulder that cares...

But with the release of these emails and data, there's definitely some suspicious book-cooking going on. All the more reason to take our time with policies that will make us all poorer, raise energy costs, and drive jobs away.

Yet that's exactly what you're willing to do despite the mountain of Evidence. Proof is for Mathematics, not Science.

 

[spidey07]

It's getting deeper. The Harry_Read_Me.txt document contained in the leaked files shows just how flawed their data was. It's looking more and more like Climategate is going to show just how bad the science was.

http://www.cbsnews.com/blogs/2009/11/24/taking_liberties/entry5761180.shtml

I am seriously worried that our flagship gridded data product is produced by Delaunay triangulation - apparently linear as well. As far as I can see, this renders the station counts totally meaningless. It also means that we cannot say exactly how the gridded data is arrived at from a statistical perspective - since we're using an off-the-shelf product that isn't documented sufficiently to say that. Why this wasn't coded up in Fortran I don't know - time pressures perhaps? Was too much effort expended on homogenisation, that there wasn't enough time to write a gridding procedure? Of course, it's too late for me to fix it too. Meh.

I am very sorry to report that the rest of the databases seem to be in nearly as poor a state as Australia was. There are hundreds if not thousands of pairs of dummy stations, one with no WMO and one with, usually overlapping and with the same station name and very similar coordinates. I know it could be old and new stations, but why such large overlaps if that's the case? Aarrggghhh! There truly is no end in sight... So, we can have a proper result, but only by including a load of garbage!

One thing that's unsettling is that many of the assigned WMo codes for Canadian stations do not return any hits with a web search. Usually the country's met office, or at least the Weather Underground, show up – but for these stations, nothing at all. Makes me wonder if these are long-discontinued, or were even invented somewhere other than Canada!

Knowing how long it takes to debug this suite - the experiment endeth here. The option (like all the anomdtb options) is totally undocumented so we'll never know what we lost. 22. Right, time to stop pussyfooting around the niceties of Tim's labyrinthine software suites - let's have a go at producing CRU TS 3.0! since failing to do that will be the definitive failure of the entire project.

Ulp! I am seriously close to giving up, again. The history of this is so complex that I can't get far enough into it before by head hurts and I have to stop. Each parameter has a tortuous history of manual and semi-automated interventions that I simply cannot just go back to early versions and run the update prog. I could be throwing away all kinds of corrections - to lat/lons, to WMOs (yes!), and more. So what the hell can I do about all these duplicate stations?...

 

[brencat]

Yet that's exactly what you're willing to do despite the mountain of Evidence. Proof is for Mathematics, not Science.

Most people vote on wallet issues. And if you want to take my money in the form of lost jobs, higher energy bills and taxes, and lost GDP for my country, you had better show me proof. Enough of this leftist touchy-feel-good emotion-driven policy bullsh*t.

 

[sandorski]

Most people vote on wallet issues. And if you want to take my money in the form of lost jobs, higher energy bills and taxes, and lost GDP for my country, you had better show me proof. Enough of this leftist touchy-feel-good emotion-driven policy bullsh*t.

Fail. You're missing out on a huge Industry. Luckily for you, other Americans will be doing it anyway, addressing the Issue, creating Jobs, and making $Billions.

 

[shira]

Like I said we'll see in 60 years time or so.

The climate deniers will never "see;" they'll insist that any warming (assuming they even accept that there IS actual warming) has nothing to do with mankind. They'll insist that all of science has been co-opted by eco-extremists, that climate researchers can receive research funding only if they "get with the global-warming plan," and that all studies showing significant anthropogenic contributions to climate change are filled with fraud.

In other words, what we have here is a classic conspiracy theory. No amount of evidence will ever convince conspiracy-theory advocates that there is no conspiracy. Already, they insist NASA is in on it, and the IPCC, and pretty much any other worldwide scientific body that proclaims the legitimacy of ACC (which is essentially ALL scientific bodies). They reject data from - for example - wikipedia because "it's run by the fear-mongers." Any evidence you present is going to be rejected out of hand. They're immune to rational discussion. They're lost causes.

 

[spidey07]

The climate deniers will never "see;" they'll insist that any warming (assuming they even accept that there IS actual warming) has nothing to do with mankind. They'll insist that all of science has been co-opted by eco-extremists, that climate researchers can receive research funding only if they "get with the global-warming plan," and that all studies showing significant anthropogenic contributions to climate change are filled with fraud.

In other words, what we have here is a classic conspiracy theory. No amount of evidence will ever convince conspiracy-theory advocates that there is no conspiracy. Already, they insist NASA is in on it, and the IPCC, and pretty much any other worldwide scientific body that proclaims the legitimacy of ACC (which is essentially ALL scientific bodies). They reject data from - for example - wikipedia because "it's run by the fear-mongers." Any evidence you present is going to be rejected out of hand. They're immune to rational discussion. They're lost causes.

Are you dizzy yet?

There's no talk of conspiracy. Just that the scientists and institute of the leading source of information on global warming fudged their data and now there is proof.

 

[shira]

Then maybe you shouldn't of targeted groups that most people would disagree with when you said "quote-mining" and instead of just said "the shady practices different groups participate in." You don't do yourself any favors when you only target the people you disagree with when the people you do agree with do similar practices.

But you see, it's the anti-science crowd that has this practice down to a (excuse the irony) science. Sure, I see out-of-context quotes all the time, but it's usually just an isolated example of limited importance. The evolution naysayers CLEARLY had an organized strategy to use out-of-context quotes from Darwin to imply Darwin himself didn't believe in natural selection. I saw the same quotations time and time again. Even when corrected on their distortions - even when shown the full quotation that made clear what Darwin actually was saying - they continued to use the same out-of-context quotes, making the same dishonest claims. In other words, they knew damn well what they were doing; they knew damn well that Darwin believed in natural selection; but they didn't care - their purpose was to sway the public, and the truth be damned.

I see this exact same truth-be-damned strategy at work with respect to these hacked emails. Anyone who's bothered to look into this matter more fully understands that the emails have nothing to do with climate fraud. (Read today's Washington Post editorial
http://www.washingtonpost.com/wp-dyn/content/article/2009/11/24/AR2009112403549.html
for a fair-minded appraisal of what these emails really mean.) Yet the climate-denial crowd is playing this incident for all it's worth. They continue to pretend that the emails reveal scientific fraud at work. Even worse, they pretend that what a handful of scientists are falsely alleged to have done means that ALL of climate research is fraudulent, an extrapolation that any principled person agrees is absurd.

If you can provide examples of the left engaging in an organized campaign that uses out-of-context quotations in willful disregard of the truth in order to sway public opinion, please let me know, and I'll condemn that behavior just as I condemn the climate-denial crowed (and I'll amend my future posts to not single out the right). Until then, the right gets the lion's share of my wrath.

 

[spidey07]

Shira,

Are you completely ignoring the harry_read_me.txt document about the database their entire study is based off of? It's not just e-mails that were released, it includes the data and the code.

Here's a link to the leaked file for you and everybody to see.
http://di2.nu/foia/HARRY_READ_ME-0.html

 

[Mxylplyx]

How come the effects of mass deforestation going on throughout the world, particularly in the recent era of global commodity trading for lumber and agricultural products, seems to be overlooked?

 

[jonks]

But you see, it's the anti-science crowd that has this practice down to a (excuse the irony) science.

I do wonder what the crossover is between the anti-gw crowd and the ID crowd.

 

[IGBT]

It's getting deeper. The Harry_Read_Me.txt document contained in the leaked files shows just how flawed their data was. It's looking more and more like Climategate is going to show just how bad the science was.

http://www.cbsnews.com/blogs/2009/11/24/taking_liberties/entry5761180.shtml

..just a matter of time before the spectre of criminal culpability sets in. these "scientists" will start ratting each other out. some will find relief on a three legged stool and a noose.

 

[shira]

Shira,

Are you completely ignoring the harry_read_me.txt document about the database their entire study is based off of? It's not just e-mails that were released, it includes the data and the code.

Here's a link to the leaked file for you and everybody to see.
http://di2.nu/foia/HARRY_READ_ME-0.html

Yeah? So?

I looked at one random email entry. Turns out a climatologist was attempting to determine why data from Vietnam/Laos from December, 1991 was (apparently) too HIGH. Let's follow the fraudulent activity:

Then Laos/Vietnam. Here we have an anomalously high peak for 1991 DJF. Used getllstations.for
to extract all stations in a box around Laos & Vietnam (8 to 25N, 100 to 110E), a total of 96
stations from Thailand, Vietnam, Laos, Kampuchea, and China. Eeeek. Tim O's program only worked
with boxes though. Also, I'm not 100% sure which year DJF belongs to in Tim's world.. hopefully
it's the December year (as it was the fourth column in his plot table). However.. plotted *all*
the data as overlapping years, and there is no trace of a spike in DJF. Uh-oh.

I'm not actually convinced that the 'country box' approach is much cop. Better to examine each
land cell and automagically mark any with excessions? Say 5 SD to begin with. Could then be
extra clever and pull the relevant stations and find the source of the excession? Of course, this
shouldn't happen, since there is a 4SD limit imposed by anomdtb.f90 for precip (3SD for others).

Wrote vietlaos.for to run through the lists of Vietnam and Laos cells (provided by Tim O) and
extract the DJF precip values for each (from the 1901-2006 gridded file). It then calculates the
standard deviation of each series, normalises, and notes any values over 6.0 SDs (1991 onwards).

Result.. some very high values (up to 11.3 standard deviations!) in 1991/2. Worst cells:
Row Column Index StdDev
212 571 273 11.21
213 571 273 11.30
214 571 273 10.15
212 572 273 11.11
213 572 273 11.20
214 572 273 10.58
212 573 273 10.84
213 573 273 11.10
212 574 273 10.76
215 572 273 10.06
214 573 273 10.53
213 574 273 10.94
214 574 273 10.44
212 575 273 10.65
213 575 273 10.66
211 576 273 10.96
212 576 273 10.51

Index 273 can be related to time as follows. The series begins in 1901 and we take three values
per year (J,F,D). So 1990 would be the 90th year and the 268th-270th values. Thus 273 = Dec 1991.

The cells are all contiguous, implying a single station's influence via the gridding process:

570 571 572 573 574 575 576
211 n/a n/a 6.37 7.56 8.36 9.71 10.96
212 n/a 11.21 11.11 10.84 10.76 10.65 10.51
213 5.52 11.30 11.20 11.10 10.94 10.66 n/a
214 5.34 10.15 10.58 10.53 10.44 n/a n/a
215 4.37 9.97 10.06 n/a n/a n/a n/a

'n/a' means the cell isn't in the Laos or Vietnam areas.

The 'epicentre' of the anomaly looks to be cell (213,571), which is in the Laos file:
Box Column Row Lon Lat
205773 571 213 105.75 16.75

So we're looking for stations in the vicinity of 105.75E, 16.75N. Well the precip database has a
total of EIGHT Laos stations, so that should be straightforward:

4893000 1990 10210 304 LUANG PRABANG LAOS 1951 2006 -999 -999.00
4893800 1920 10170 323 SAYABOURY LAOS 1969 2006 -999 -999.00
4894000 1800 10260 170 VIENTIANE LAOS 1941 2006 -999 -999.00
4894600 1738 10465 152 THAKHEK LAOS 1989 2006 -999 -999.00
4894700 1660 10480 155 SAVANNAKHET LAOS 1970 2006 -999 -999.00
4894800 1670 10500 184 SENO LAOS 1951 2006 -999 -999.00
4895200 1568 10643 168 SARAVANE LAOS 1989 2006 -999 -999.00
4895500 1510 10580 93 PAKSE LAOS 1968 2006 -999 -999.00

Well, SENO has to be the prime candidate. Unfortunately, this is from SENO:

4894800 1670 10500 184 SENO LAOS 1951 2006 -999 -999.00
<snip>
1989 0 0-9999 1910-9999 1010 4450 2690 2880 1340 0 0
1990 60 1560 150 420 1110 4830 3620 3690-9999 780 30 0
1991 0 0 400 0 690 1907 1890 5308 3238 805 0 366
1992 488 280 50 80 1883 2503 2644 2935 2039 131 0 89
1993 0 0 139 280 2324 1163 1949 4460 2145 0 29 0

A most undistinguished set. So, the net widens:

Gee. He tried to actually determine which Laos station was the source of the anomaly, rather then just accepting the too-high value. That seems contrary to a researcher who wants to "max out" temperature results. He genuinely appears to be trying to eliminate error, not introduce it. What a strange thing for a data-fabricator to do. Anyway, back to the conspiracy:

4894700 1660 10480 155 SAVANNAKHET LAOS 1970 2006 -999 -999.00
<snip>
1989-9999 0-9999-9999 1080-9999-9999-9999-9999 1490-9999-9999
1990 30-9999 240-9999-9999-9999 1920-9999-9999-9999-9999 0
1991 0 0 127 49 952 2508 1681 4034 4006 1690 0 338
1992 324 338 93 691 1932 2344 2048 4464 756 607 0 197
1993 0 5 335 263 2665 921 2884 2204 1834 17 23 0

..nope..

4894600 1738 10465 152 THAKHEK LAOS 1989 2006 -999 -999.00

1989-9999 0-9999-9999 2030-9999-9999-9999-9999 1490-9999-9999
1990 10-9999 520-9999-9999-9999-9999-9999-9999-9999-9999 0
1991 0 0 905 119 861 6058 3578 7092 2417 373 0 324
1992 105 318 125 456 2140 2978 4623 4595 3376 425 0 854
1993 0 108 52 1343 5835 2999 6285 4375 1017 467 8 0

..nope.. unless these values *are* unusual? Let's look at the highest two Decembers from
each station:

4893000 1990 10210 304 LUANG PRABANG LAOS 1951 2006 -999 -999.00
1992 193 911 0 497 657 1246 2971 2837 929 584 95 1372
1994 0 54 1107 291 1702 2436 2025 3636 1516 316 185 816

4893800 1920 10170 323 SAYABOURY LAOS 1969 2006 -999 -999.00
1992 411 719 0 816 754 1252 2573 1671 1686 991 351 879
1994 0 208 1695 503 2262 1607 1743 2562 3205 118 193 454

4894000 1800 10260 170 VIENTIANE LAOS 1941 2006 -999 -999.00
1971 0 70 140 340 2940 2750 2890 2260 1630 1030 0 180
1992 381 273 11 424 2372 4878 4381 3676 3091 630 0 212
1994 0 300 921 322 2685 2725 4698 1932 4000 3031 1016 166 (inc for comparison with previous)

4894600 1738 10465 152 THAKHEK LAOS 1989 2006 -999 -999.00
1991 0 0 905 119 861 6058 3578 7092 2417 373 0 324
1992 105 318 125 456 2140 2978 4623 4595 3376 425 0 854
1994 0 612 952 558 1697 7092 5121 4276 2428 486 20 2 (inc for comparison with previous)

4894700 1660 10480 155 SAVANNAKHET LAOS 1970 2006 -999 -999.00
1991 0 0 127 49 952 2508 1681 4034 4006 1690 0 338
1992 324 338 93 691 1932 2344 2048 4464 756 607 0 197
1994 0 734 390 494 1381 3377 1525 5651 1881 600 0 0 (inc for comparison with previous)

4894800 1670 10500 184 SENO LAOS 1951 2006 -999 -999.00
1971 0 880 130 370 1270 4010 2200 2860 1930 410 0 140
1991 0 0 400 0 690 1907 1890 5308 3238 805 0 366
1992 488 280 50 80 1883 2503 2644 2935 2039 131 0 89 (inc for comparison with previous)
1994 0 532 318 969 2065 1937 1197 4552 1934 197 0 0 (inc for comparison with previous)

4895200 1568 10643 168 SARAVANE LAOS 1989 2006 -999 -999.00
1992 287 33 52 222 1072 5444 2998 8899 2243 1070 0 0 (inc for comparison with previous)
1994 0 10 354 686 1743 3387 5829 3254 4219 408 41 4 (inc for comparison with previous)
1998 26 619 0 574 2386 2871 1530 2308 2680 913 463 73
2005 0 0 120 1230 1990 2860 4350 8060 3770 280 140 70

4895500 1510 10580 93 PAKSE LAOS 1968 2006 -999 -999.00
1972-9999-9999-9999-9999-9999-9999-9999-9999 2610 870 280 140
1992 166 101 0 210 665 1898 2574 6448 2942 648 10 31 (inc for comparison with previous)
1994 0 0 134 220 2537 3596 5161 5384 7693 1513 236 94


Summary: LUANG PRABANG shows a significant anomaly of 1372 for Dec 1992. Unfortunately, this
finds echoes both temporal (1994 has 816) and spatial (SAYABOURY's 1992 is 879). So, if these
values are causing the spike, it's genuine (if exaggerated in a way yet to be determined).

So, the conspirator concludes that the temperature may be exaggerated, but is a genuine spike. But the researcher continues to try to get to the bottom of it. What a strange conspirator. You'd think he'd be happy to "justify" the spike. But he seems to actually want to eliminate error, even high error.

Wrote vietlaos2, to gather data from the cells AND stations. It also gets the climatology. Initially
it only gathered 13 stations with data in 1991/2, using 'VIETNAM' and 'LAOS' to select on country
name. However, taking the cell [214,574] in December 1991 as the peak incident, we can use those
coordinates (17.25N, 107.25E) to centre a bounding box for station selection. A box 10degs square
yields only 17 stations, none of which have anything remotely spikey in Dec 1991. A box 20degs
square (some would say unfeasibly large) yields 98 stations, one of which does have a bit of a spike
in Dec 91.. not impressively so though, and it's a long way away:

4855200 853 9993 3 NAKHON SI THAMMARAT THAILAND 1912 2000 -999 -999.00

Over 10.5 degrees South and over 7 degrees West of the target cell. Not very convincing, especially
as closer stations are bound to have masked it.

One FINAL try with vietlaos3.for. Just looking at December, now, and getting the original station
normals as well as the climatological ones. The whole chain. This proves to be surprisingly
complicated.

On a parallel track (this would really have been better as a blog), Tim O has found that the binary
grids of primary vars (used in synthetic production of secondary parameters) should be produced with
'binfac' set to 10 for TMP and DTR. This may explain the poor performance and coverage of VAP in
particular.

Back to VietLaos.. the station output from vietlaos3.for had a couple of stations with missing
anomaly values:

LAT LON ALT NORM VAL ANOM
17.15 104.13 171.00 29.00 62.00 -9999.00
15.80 102.03 182.00 45.00 40.70 -9999.00

I eventually worked out that I hadn't collapsed a universal probability, it was just the 4 standard
deviation screen in anomdtb (4 for precip, 3 for temp). To confirm, I did a short anomdtb run (just
for 1991) with the sd limit set to 10, and sure enough:

17.15 104.13 171.0 2037.900024835600
15.80 102.03 182.0 804.400024840300

They both look high enough to trigger the 4sd cap. However, since the spike we're investigating is
from a regular process run, where that limit was in place, we can't use those values. Program is thus
amended to omit any stations without anomalies (for Dec 1991)

Next issue is to make sense of the output. The first line from the station file is (headings added):

LAT LON ALT NORM VAL ANOM
22.60 114.10 25.00 29.00 21.60 -25.50

Remembering it's percentage anomalies! So 25.5% of 29 is 29*.255 = 7.395. Add that to 21.6? 29.0 🙂

By contract, the cell file looks like this:

ROW COL LAT LON VAL NORM
220 561 20.25 100.75 12.90 15.00

There are 63 stations and 204 cells (196 when missing values (sea) eliminated). I guess one approach
would be to grid the anomalies, to see if a peak is visible. I did. It is. The simple interpolation
in Matlab puts the peak at 17.25N, 105.25E - matches the grid peak for lat and a little west for lon.
The nearest high station anomaly is 2369.2, that's from:

4838300 1653 10472 138 MUKDAHAN THAILAND 1934 2000 -999 -999.00
6190 34 127 290 907 1813 2900 2271 3353 2596 886 84 13
1934 0 100 0 500 3150 2940 2460 2980 3320 350 0 20
1935 0 0 0 440 1920 1560 3220 580 1770 0 170 0
1936 0 0 820 0 2320 1900 3460 810 2120 0 0 0
1937 0 0 350 660 3640 740 1920 2890 4470 330 0 0
1938 0 0 550 1300 730 1720 2340 400 2030 810 0 0
1939 0 280 700 230 1320 420 2480 4190 2130 0 0 0
1940-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999
1941 0 0 530 590 1800 2710 420 2790 650 750 0 0
1942 0 0 540 660 1650 3200 1200 1730 1990 0 0 0
1943 0 0 1600 1300 1960 1880 2000 2200 2600 0 0 0
1944 0-9999 0 320 2210 1040 1700 2500 2150 820 50 0
1945 70 600 0 340 0 2470 3400 2780 1620 20 330 500
1946 0 0 1360 0-9999 1720 1070 3330 2870 1260 0 0
1947 0 180 50 1390 3200 1530 3520 1150-9999 50 0 0
1948-9999-9999 0 1630 3520 1040 2900 3980 2160 380 10 0
1949 0 200 170 470 3000 2720 3110 4920 360 690 90-9999
1950 0 70 0 250 1610 2090 1040 1390 3500 1960 20 0
1951 0 340 770 1380 530 3380 1590 1950 3580 1430 20 0
1952 0 0 1170 660 1640 3160 2320 4150 3510 860 30 0
1953 260 110 430 630 1010 2200 1480 2780 1180 310 10 0
1954 460 10 30 1100 1950 2870 1120 2640 4220 620 0 0
1955 0 0 280 580 2180 4100 2900 2570 1810 270 20 0
1956 0 420 150 1000 3000 2930 3980 3840 2020 220 0 0
1957 0 30 1210 630 1690 2130 2090 3030 3240 460 0 0
1958 70 50 10 1090 1060 1690 2670 910 2750 700 0 0
1959 0 430 730 290 2300 1540 2080 2030 3910 280 0 0
1960 0 190 550 650 1230 1750 3750 5090 2190 700 90 0
1961 0 0 590 660 2190 5880 2150 4310 4030 1140 0 0
1962 0 20 120 880 2200 2690 2780 4770-9999 360 50 0
1963 0 0 610 600 1010 3480 2130 3410 1250 220 150 0
1964 0 0 740 910 3370 2600 630 2050 4700 1120 20 0
1965 0 250 660 780 2120 2700 2110 2810 2210 1350 0 0
1966 0 610 310 730 3340 1370 3100 4010 2020 510 40 110
1967 0 0 50 870 1810 1800 1540 1960 3270 150 130 0
1968 10 70 50 170 1770 2320 1140 2360 5140 700 0 0
1969 0 20 290 260 1850 1990 3430 2060 3470 290 30 0
1970 0 10 90 1150 2210 3620 2610 4310 1290 340 10 0
1971 0 730 570 740 2130 3580 4060 2100 3240 510 30 170
1972 0 550 460 1280 1040 3470 3250 3640 2980 2340 20 0
1973 0 0 10 1080 2650 1990 2460 2050 2090 190 0 0
1974 400 0 60 2160 1160 2520 3070 6110 1920 570 260 0
1975 20 350 360 410 2200 3340 3230 3560 940 520 20 40
1976 0 210 380 1700 1160 1460 2430 3720 3250 780 60 0
1977 20 10 90 1000 620 620 1470 3980 4010 100 0 0
1978 0 100 920 650 1710 3690 2960 4420 2190 110 0 0
1979 10 140 50 900 2000 4230 1230 2540 2910 0 0 0
1980 0 50 190 1040 1440 3490 3310 930 6130 1830 170 20
1981 0 210 220 720 2630 4730 2490 1750 610 1260 90 0
1982 0 0 290 840 1330 2160 390 4390 3400 1720 370 0
1983 90 30 0 550 1360 2700 830 5200 1380 1680 0 0
1984 10 0 350 1270 2030 2290 2900 3880 2130 1380 650 0
1985 380 50 170 860 1100 4270 1580 3350 900 1170 0 0
1986 0 0 120 1650 2120 2210 1830 2980 1760 1700 240 10
1987 0 110 290 360 1090 4210 2670 3640 2140 1040 20 0
1988 0 30 90 1170 1130 1790 1800 3580 740 1730 0 0
1989-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999
1990-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999
1991 0-9999 105 226 1370 2079 1452 4190 3799 1610-9999 321
1992 328 314 150 637 1968 1906 2366 4973 1287 238 0 216
1993-9999 5 476 768 2438 1169 3671 2463 2215 13 22-9999
1994 0 781 274 409 1837 2297 1625 5755 1709 216-9999-9999
1995 0 140 834 672 1556 1606 4439 2848 681 857 69 0
1996 12 2 660 2394 1566 1526 1960 3350 4843 724 476-9999
1997 35 321 458 642 1154 2832 1197 4071 1722 1800 0-9999
1998 0 346 154 241 2174 3348 813 2153 2231 276 85 37
1999 63 0 182 1025 3449 1207 3681 1570 2628 299 109-9999
2000-9999 95 48 2742 2816 1852 1725 1903 2903 391 0 0

Note that the Dec 1991 value is anomalous, but not as extreme as the 1945 datum,
which would get the same treatment with normals and climatologies, so should
produce an even bigger spike for 1945 DJF! Unless of course it's screened out by
the 4SD rule.. which it is! Well - no value in pre.1945.12.txt for this location.

Anyway.. this is the highest value in the Vietnam/Laos cells for Dec 1991:

ROW COL LAT LON VAL NORM
198 571 9.25 105.75 63.50 130.00

With a normal of 130, that makes the anomaly -48.85. Now I'm confused. How can
an anomalously high value be well below the 61-90 mean? Aaarrgghhhh. Perhaps I
should look at the highest anomaly. That turns out to be 80, from here:

216 563 18.25 101.75 1.80 1.00

Not exactly a show stopper. Time to look at the .glo files, which glo2abs processes
into absolutes. Here's a Far-Eastern region with a spike:

>> glod3(210:216,567:573)

567 568 569 570 571 572 573
216 1393.6 1791.6 1757.4 1723.2 1674.5 1553.2 1431.9
215 1501.7 1899.8 1927.3 1893.1 1786.3 1665 1505.3
214 1609.9 2007.9 2097.2 2019.5 1885.4 1712.8 1540.2
213 1359.4 2116.1 2252.6 2092.9 1920.3 1747.7 1575.1
212 80.145 1195.5 1796.1 1882 1955.2 1782.6 1610
211 -6.125 -36.614 563.99 649.87 735.75 821.63 907.5
210 -59.833 -90.333 -89.649 -83.283 -76.929 -70.576 -64.223

The spike is at [213,569]. Yes, I know, it's the n-th set of coordinates. You should see the
plots! But looking at the anomalies is the closest we'll get to what Tim's program was doing,
ie, calculating DJF standard deviations. Or something. Now, the coordinates are 16.75N, 104.75E.
And wouldn't you know it, our prime suspect (see above) is on top of it:

4838300 1653 10472 138 MUKDAHAN THAILAND 1934 2000 -999 -999.00

So OK, here we go with the full run-down for December 1991, in the 16.75N,105.75E region:

TYPE VALUE COMMENT
Raw data: 321 Highest unscreened December for this station (67 years)
Normal: 13 Looks right - of course, very low for the target data!
Anomaly: 2369.2 Correctly calculated
Gridded anomaly: 2252.6 Believable interpolation
Gridded actual: er... Strangely, it seems to be 0.

Ah well - had enough. It looks like it's an extreme but believable event in a Thai station, let's
leave it like that.

After all that work, after looking a spikes from other locations for comparison, the conspirator grudgingly decides to accept the Thai spike is valid.

Summary: A climate "conspirator" spends hours and hours of analysis trying to detemine why a seeminly too-high value from Thailand occurred. Somehow, this doesn't come across like someone trying to falsify data. This sounds like someone trying to get the data as correct as possible.

Edit: Oh, my bad. Did I forget to quote-mine the above long excerpt to make it appear that something nefarious was going on? Or should I have searched and searched for just the RIGHT email, and quote-mined from that email? Silly me, I took an entire "evening in the life" of a climate researcher and discovered . . . . . a researcher who really, really cares about getting the data right. Amazing!!!

 

[Patranus]

a researcher who really, really cares about getting the data right.

I am pretty sure that is the point.
You don't "get data right".
There is a difference between looking at the data and coming to a conclusion and manipulating data to fit a pre-existing conclusion.

 

[IGBT]

I am pretty sure that is the point.
You don't "get data right".
There is a difference between looking at the data and coming to a conclusion and manipulating data to fit a pre-existing conclusion.

explains why algore(al gore) would never debate the issue. he knew in his heart of hearts it's a scam and a hoax. it was easier to let the willing accomplices flack catch while he maintains his "above it all" condescension.

 

[shira]

I am pretty sure that is the point.
You don't "get data right".
There is a difference between looking at the data and coming to a conclusion and manipulating data to fit a pre-existing conclusion.

You really ARE the village idiot. There's no indication whatsoever that this scientist was attempting to fit the data to a pre-existing conclusion. He CLEARLY was (1) identifying what he though was an anomalous HIGH (not low) termperature, then (2) was performing a series of analyses using both contemporary data from nearby regions and also using historical data to determine if the reported result truly was erroneous. If you read into what this scientist was doing that he was working toward a pre-determined conclusion, you're beyond help; you're delusory.

Scientists don't just collect data and unquestioningly use it. They test it to ensure there haven't been collection errors. A measurement of, say, 150 degrees in Antartica would be flagged as an error. Less obviously, a series of measurements warmer or colder than surrounding regions would be checked to ensure the data was legitimate.

Errors can arise for all sorts of reasons. Errors in measuring equipment, for example. Or placing equipment near strong absorbers or radiators. Or near areas with geothermal activity.

Also, observed results can occur for reasons other than obvious ones. For example, the article I posted two days ago about the reported loss of glacial mass in East Antartica MAY be due to melting consequent to global warming. Or there may have been no melting at all - the result may simply be due to random snowfall variations, leading to the erroneous conclusion that there was lost mass. Only time will tell which reason (or some other reason) is the cause.

You seem to think that when data is collected, it's perfect right off the bat. But then, you obviously have no knowledge of science.

 

[shira]

explains why algore(al gore) would never debate the issue. he knew in his heart of hearts it's a scam and a hoax. it was easier to let the willing accomplices flack catch while he maintains his "above it all" condescension.

You, like Patranus, obviously revel in your ignorance. Only people like you and Patranus think that "getting the data right" (meaning removing measurement errors) means fudging data to fake a trend.

I give up dealing with cretins like your kind. You can't even understand what's right in front of your face.

 

[shira]

I do wonder what the crossover is between the anti-gw crowd and the ID crowd.

Just look at the response of Patranus to evidence of a typical scientist error-checking data and you'll see clear evidence that the same, willful know-nothing attitude of the ID crowd. They desperately misconstrue even the most obvious truths.

It's frightening to contemplate how utterly devoid of intellectual honesty these people are.

 

[dmcowen674]

The changes will be so gradual that most won't even notice them.

Let's put your ass at sea level and tell me how "gradual" it is.

 

[boomerang]

Happy Festivus!