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Clear Climate Code

The 1990s station dropout does not have a 

warming effect

Posted by drj | Filed under announcement

Tamino gives his results for his GHCN based temperature reconstruction. It is well 

worth reading. He also gives a comparison between stations that are reporting after 

1992, and those that “dropped out” before 1992. He concludes that there is no 

significant difference in the overall trend. In other words refuting the claim that the 

1990s station dropout has a warming effect. His results are preliminary and for the 

Northern Hemisphere only.

Tamino’s analysis use only the land stations; in order to write this blog post I tweaked 

ccc-gistemp so that we can produce a land index (python tool/run.py -s 1-3,5

now skips step 4, avoids merging in the ocean data, and effectively produces a global 

average based only on land data).

It is very easy to subset the input to ccc-gistemp and run it with smaller input 

datasets. So in this case I can split the input data into stations reporting since 1992, 

and those that have no records since 1992, and run ccc-gistemp separately on each 

input. I created tool/v2split.py to split the input data. Specifically I ran step 0

(which merges USHCN, Antarctic, and Hohenpeissenberg data into the GHCN data) to 

create work/v2.mean_comb then split that file into those stations reporting in 1992 

and after, and those not reporting after the cutoff. Then I ran steps 1,2,3, and 5 of ccc

-gistemp to create a land index:

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http://clearclimatecode.org/the-1990s-station-dropout-does-not-have-a-warming-effect/ 7/29/2010
It is certainly not the case that the warming trend is stronger in the data from the post

-cutoff stations. [edit 2010-03-22: In a subsequent post I add trend lines to this 

chart]

The differences between these results and Tamino’s are interesting. Both show good 

agreement for most of the 20th century. These data show more divergence than 

Tamino’s in the 1800’s. Is that because we’re using Southern Hemisphere data as 

well, or is it because of the difference in station combining? Further investigation is 

merited.

We hope to make “experiments” of this sort easier to perform using ccc-gistemp and 

encourage anyone interested to download the code and play with it.

Update: Nick B obliges with a graph of the differen Update ces:

Clear Climate Code » Blog Archive » The 1990s station dropout does not have a warming... Page 2 of 16

http://clearclimatecode.org/the-1990s-station-dropout-does-not-have-a-warming-effect/ 7/29/2010
Tags: gistemp

Permalink | Comments (41) | Feb 26, 2010 

41 Responses to “The 1990s station dropout does not have a 

warming effect”

carrot eater Says: 

February 26th, 2010 at 4:23 pm

1.

Re the 19th century difference: Even in the NH, undersampling will be a 

bit worse back then. But take the SH data (already undersampled) and 

split it into two bits, and it could be pretty bad.

So I think the difference will be how the grid boxes are used, along with 

using SH. Tamino is using coarse grid boxes. GISS is using distanceweighted interpolation to points within smaller grid boxes. 

With undersampling, this will likely have some impact. With wellsampled data, it won’t matter.

Zeke Hausfather Says: 

February 26th, 2010 at 4:39 pm

2.

Thanks for the timely analysis drj.

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http://clearclimatecode.org/the-1990s-station-dropout-does-not-have-a-warming-effect/ 7/29/2010
Any chance it would be easy to whack another mole by generating a 

similar graph for all urban stations in the U.S. and all rural stations, to 

tackle the contrarian argument du jour: 

http://wattsupwiththat.com/2010/02/26/a-new-paper-comparingncdc-rural-and-urban-us-surface-temperature-data/ ?

lucia Says: 

February 26th, 2010 at 4:53 pm

3.

Is that because we’re using Southern Hemisphere data as well, or is it 

because of the difference in station combining? Further investigation is 

merited.

Are there fewer thermometers in the 1880? Is mal-distribution more 

obvious? If the answers are yes, the difference in the mean may just be a 

consequence of uncertainty in the mean using a smaller number of 

measurements aggravated by sub-optimal distribution for determining 

the area averaged temperature. 

Also, because you use the anomaly method, unless you did something 

unconventional, your two versions are forced to match on average 

during the shared baseline. If there are real differences arising from 

using different stations, the consequence of those differences will be 

more visible further away from the baseline periods. 

I would not be at all surprised to see the various versions of computing 

the surface trend diverging as the trends go back in time.

drj Says: 

February 26th, 2010 at 5:04 pm

4.

@lucia: I have access to same data as you do when it comes to 

answering the thermometers question, but I assume you also know the 

answer.

And yes, of course poor sampling will lead to more divergence, in 

probability.

GISTEMP uses the anomaly method, and ccc-gistemp is an emulation of 

it, so yes. And yes, that will force the average over the base period to 

match. The choice of base period is irrelevant to the trend, however.

drj Says: 

February 26th, 2010 at 5:08 pm

5.

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@Zeke: Not until Monday, and maybe not then. If however you have a 

handy list of Rural and Urban stations, do please cut the input data 

yourself!

carrot eater Says: 

February 26th, 2010 at 5:15 pm

6.

Zeke: You might be asking the wrong guys. That particular assertion is 

about the USHCN adjustments, I’m pretty sure. Those adjustments are 

already baked in, before GISS or ccc starts doing anything.

You’ll want to go to the USHCN web page, get the raw data, TOB 

adjusted data, and final adjusted data, and go from there. If you must 

cheat, the NCDC has made the code available for their adjustments, but 

I think simple comparisons of the raw and final sets would suffice, for 

starters.

lucia Says: 

February 26th, 2010 at 5:38 pm

7.

@drj–

I have access to same data as you do when it 

comes to answering the thermometers 

question, but I assume you also know the 

answer.

The answer to what? 

I suspect we are talking at cross purposes because I used rhetorical 

questions, which I actually know should be avoided in blog comments. 

They cause confusion, and that’s my fault.

What I meant to communicate was that to extent that the answer to my 

rhetorical questions are yes (and I suspect they are even without looking 

or running any code), I think we should expect see divergences in 

computed anomalies in the early thermometer record.

I appears we agree on the effect of statistical uncertainty on divergence 

back in the early record. My take is that statistical uncertainty may be 

sufficient explanation of the approximately 0.2C difference in 

Clear Climate Code » Blog Archive » The 1990s station dropout does not have a warming... Page 5 of 16

http://clearclimatecode.org/the-1990s-station-dropout-does-not-have-a-warming-effect/ 7/29/2010
temperature anomalies computed using the two different thermometer 

sets back in 1880-1900. [ed: corrected "1990" to "1900"]

Do we more or less agree on that? Or do you think it’s something else?

I am also saying that — without looking at the code or data — if we look 

at any T_anomaly vs. Time graph, and there are real differences (or even 

difference resulting from statistical uncertainty) those will appear larger 

far from the baseline periods. This effect should be rather data 

independent because its a direct consequence of the anomaly method. 

So, for example, if you happened to re-baselined using 1880-1900, the 

match would look poor now, and good back then. I think that sort of rebaseline would be misguided because it makes no sense to baseline to a 

period with larger measurement uncertainties– but that is what would 

happen if we did pick that period. Anyway: Once again, the reason we 

see the slight mismatch back in 1880-1900 [ed: and again] is at least 

partly related to the choice of baseline. 

Do we agree? 

So, it seems to me the fact that differences between results using precut off and post-cut off thermometers are visible way back in 1900 is 

both because 

a) we know there were fewer thermometers so ‘noise’ alone can cause 

this to occur even if there is no bias associated dropping out 

thermometers and 

b) the anomaly method does have a tendency to force agreement in the 

average during the baseline period. So no matter the cause of 

differences, they will be more noticeable far from the baseline period.

Anyway, I think your post is useful. To my knowledge that makes the 

fourth post that shows the drop out in thermometers does not cause a 

bias in the long term trend.

Nick.Barnes Says: 

February 26th, 2010 at 5:42 pm

8.

Zeke: although we’re not set up to do experiments with the NCDC 

datasets, it would be very easy for us (or for you) to do a ccc-gistemp 

run without any US data. The GHCN data, which is the great 

preponderance of our input dataset, is raw.

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As for the UHI adjustments done in GISTEMP: they do not adjust rural 

stations at all. Only urban stations are adjusted, and urban stations 

which cannot be adjusted are dropped. See our current step2.py.

Zeke Hausfather Says: 

February 26th, 2010 at 5:59 pm

9.

Carrot,

Good catch. I forgot that GISS used adjusted USHCN (but raw GHCN) 

data as inputs.

cce Says: 

February 28th, 2010 at 8:06 am

10.

Off topic, but I noticed that GISS has switched to using night lights for 

all of its urban adjustments, not just the US48. Are you guys privy to 

those changes?

They write:

January 16,2010:The urban adjustment, previously based on satelliteobserved nightlight radiance in the contiguous United States and 

population in the rest of the world (Hansen et al., 2001), is now based 

on nightlight radiances everywhere, as described in an upcoming 

publication. The effect on the global temperature trend is small, that 

change reduces it by about 0.005 °C per century. 

http://data.giss.nasa.gov/gistemp/updates/

cce Says: 

February 28th, 2010 at 8:18 am

11.

Also, I noticed with the newest USHCN_V2 data, GISTEMP’s lower 48 

analysis shows a bit more warming that it had previously. In fact, both 

1998 and 2006 are now warmer than 1934. Hansen et al. 2001 had 

stated that they couldn’t declare a warmer year than 1934 until it was 

exceeded by at least 0.1 degrees, and the new figure for 1998 exceeds 

that (2006 is 0.1 warmer).

Nick.Barnes Says: 

February 28th, 2010 at 9:16 pm

12.

cce@10: Yes, I’d noticed the GISTEMP change, a few lines in 

STEP2/text_to_binary.py to fish a different field out of the station 

metadata file. I’ll be making a matching change in our sources before 

our 0.4.0 release.

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cce@11: GISTEMP, and ccc-gistemp, doesn’t include a “lower 48 

analysis”. 95% of the world’s population wouldn’t know what a “lower 48 

analysis” might be. I do know, and I also know it would cover about 

1/60 of the global surface, so temperatures there are not very relevant 

to our results. When you say “I noticed”, whereabouts did you notice 

this? Can you provide a link?

drj Says: 

February 28th, 2010 at 9:39 pm

13.

@cce, @Nick.Barnes: “lower 48′′ may be a reference to GISTEMP’s figure 

D. In my opinion this is wildly parochial.

cce Says: 

February 28th, 2010 at 9:40 pm

14.

The results of the lower 48 analysis is here: 

http://data.giss.nasa.gov/gistemp/graphs/Fig.D.txt

It was very relevant during the so-called “Y2K” controversy and is the 

primary reason why so many people belive the ’30s were warmer than 

recent years. That is, they confuse the US with the world.

I noticed the change when I looked at the updated graph of US 

temperature: 

http://data.giss.nasa.gov/gistemp/graphs/Fig.D.lrg.gif

1998 and 1934 have been statistically tied for a number of years (I 

believe since the TOBS improvements incorporated in 2001), but now 

1998 is back to being significantly warmer than 1934.

Zeke Hausfather Says: 

March 1st, 2010 at 6:54 am

15.

Hey now, Figure D was rather useful as a validation tool in testing my 

recent foray into gridded temperature analysis :-p

http://i81.photobucket.com/albums/j237/hausfath/Picture68.png

Comparing GISS-temp to adjusted GHCN temp for the globe is less 

interesting, since the methods are rather different.

drj Says: 

March 1st, 2010 at 9:55 am

16.

@Lucia: I do not think we are talking at cross purposes.

Clear Climate Code » Blog Archive » The 1990s station dropout does not have a warming... Page 8 of 16

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It’s fine to ask rhetorical questions (although I do have a tendency to 

answer rhetorical questions). But since you and I both know the answers 

to your rhetorical questions, I wasn’t sure what the point was.

You ask if I agree “that statistical uncertainty may be sufficient 

explanation of the approximately 0.2C difference in temperature 

anomalies computed using the two different thermometer sets back in 

1880-1990′′. Well, yes; I already said “poor sampling will lead to more 

divergence, in probability”.

You also ask if I agree that “the reason we see the slight mismatch back 

in 1880-1990 is at least partly related to the choice of baseline”. Well, 

yes, partly, but that doesn’t seem to be a very interesting statement. 

Plainly the divergence between the two series is greater in the 1800’s 

than the other parts of the series and that is not entirely a choice of 

base period. Offsetting the shorter series so that two series have the 

same average over their common period we get:

and we can see that the 1800’s still have greater divergence.

Of course we are in broad agreement, but I still think there is room for 

further investigation. In particular I think we can learn a bit more than 

“it’s just statistcal noise”: How much the difference between this analysis 

and Tamino’s is down to difference of station combination method? How 

much is down to different data? (and how much is essentially 

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uninteresting variation due to poor sampling). A northern hemisphere 

graph from ccc-gistemp will help with that.

Nick.Barnes Says: 

March 1st, 2010 at 12:46 pm

17.

cce@14: Ah, yes, figure D. That was originally in Hansen et al 1999. I am 

reading that paper now. It describes in great detail an algorithm similar, 

but not identical to the GISTEMP algorithm (the main differences I see 

are that it uses a 2-degree grid, and has less flexible UHI adjustment). I 

imagine it then area-weights the series for grid squares which include 

parts of the “lower 48′′. 

Because this figure is so very parochial, it’s not very high on my list of 

priorities to reproduce it. I might send email to GISS to ask how it is 

done. It would be the work of a few minutes to generate a US-only 

graph, by running gistemp using lower-48 data only, but that isn’t what 

Hansen et al 1999 describes. 

Without running any code at all, I can speculate that changes in this 

chart over time might be caused by the switch from USHCNv1 to 

USHCNv2 input datasets.

cce Says: 

March 1st, 2010 at 3:01 pm

18.

Nick,

I’m pretty sure the USHCNv2 changes are the cause. They began using it 

in November. I don’t think they updated the figure D graphic and table 

until February.

Also be sure to read Hansen et al. 2001 if you haven’t already, “A closer 

look at United States and global surface temperature change,” which is 

the most recent paper to describe GISTEMP.

The Blackboard » A simple model for spatially-weighted temp analysis Says: 

March 1st, 2010 at 6:03 pm

19.

[...] stations with records post-1992 to those without, to quickly 

replicate the work that Tamino and the CCC folks did on addressing E.M. 

Smith’s whole station dropout [...]

Turboblocke Says: 

March 1st, 2010 at 9:13 pm

20.

Sorry if this is mentioned elsewhere, but why are you referring to station 

drop out, when in fact it is actually old station data being added?

Clear Climate Code » Blog Archive » The 1990s station dropout does not have a warmi... Page 10 of 16

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http://www.ncdc.noaa.gov/oa/climate/ghcnmonthly/images/ghcn_temp_overview.pdf

See section 2, Sources “When possible, we tapped related projects for 

potentially 

useful data. For example, NCDC recently 

collected and processed station normals for the period 

1961–90 as a contribution to WMO (WMO 1996a). 

On occasion, a WMO member country supplied year/ 

month sequential data in addition to the 30-yr means 

and other statistics...”

carrot eater Says: 

March 2nd, 2010 at 12:02 am

21.

Turboblocke: sensible people know the history of how the GHCN was 

built. But the blog terminology was set by certain conspiracy theorists, 

so ‘drop’ is what sticks. ‘Drop’ is also less cumbersome than other 

semantic constructions.

Czy spadek liczby stacji ma wpływ na trendy? | Prognozy numeryczne 

GFS/WRF Says: 

March 2nd, 2010 at 10:27 am

22.

[...] tym, po za autorem bloga OpenMind, czy DoskonaleSzare zajęli się 

równieŜ autorzy CCC-GISTEMP. Co jest tu istotne? NałoŜono na siebie 

wykresy pokazujące przebieg odchyleń globalnych dla [...]

The Blackboard » Timeline of “The march of the thermometers” meme Says: 

March 3rd, 2010 at 3:03 pm

23.

[...] Clear Climate Code, Feb. 26, 2010 compares GISSTemp type 

calculations of global surface temperature anomalies based on the “full” 

and “cut-off” thermometer set. They find no major differences between 

the two traces. [...]

Spencer’s UHI -vs- population project – an update « Wott's Up With That?

Says: 

March 5th, 2010 at 10:29 pm

24.

[...] concluded that the bias is actually toward slightly under-reporting 

the warming. See Open Mind, Clear Climate Code, The Blackboard and 

Menne, 2010 (described at Skeptical [...]

A mistaken message from IoP? - InfoSmell.com Says: 

March 6th, 2010 at 5:40 pm

25.

Clear Climate Code » Blog Archive » The 1990s station dropout does not have a warmi... Page 11 of 16

http://clearclimatecode.org/the-1990s-station-dropout-does-not-have-a-warming-effect/ 7/29/2010
[...] more vehement in recent months even though the code base and 

data have been available for years and clearly demonstrate that the 

criticisms are [...]

Kasowanie stacji raz jeszcze | Prognozy numeryczne GFS/WRF Says: 

March 7th, 2010 at 8:34 am

26.

[...] jak metoda CAM stosowana przez CRU). MoŜna o tym przeczytać 

tutaj, a takŜe tutaj, tutaj,tutaj i tutaj. Jasne jest, Ŝe Watts i D’Aleo się 

mylą, a oskarŜenia pod adresem NOAA są [...]

Scientific replication is not rote repetition « Rearranging the Deckchairs

Says: 

March 7th, 2010 at 11:26 am

27.

[...] A replication from clear climate code [...]

Climate Update » Blog Archive » A mistaken message from IoP? Says: 

March 7th, 2010 at 7:26 pm

28.

[...] more vehement in recent months even though the code base and 

data have been available for years and clearly demonstrate that the 

criticisms are [...]

GISTEMP: High Alt, High Lat, Rural « The Whiteboard Says: 

March 8th, 2010 at 2:13 pm

29.

[...] drj @ Clear Climate Code http://clearclimatecode.org/the-1990sstation-dropout-does-not-have-a-warming-effect/ [...]

Zero Carbon » A mistaken message from IoP? Says: 

March 8th, 2010 at 9:22 pm

30.

[...] more vehement in recent months even though the code base and 

data have been available for years and clearly demonstrate that the 

criticisms are [...]

Emission Trading - Page 124 - Renovate Forums Says: 

March 8th, 2010 at 10:10 pm

31.

[...] without the actual programs, and with the same or different data 

sets as has been done by Tamino, clearclimatecode, The Blackboard, 

The Whiteboard and others. woodbe. __________________ Admission of 

the week: [...]

Steven mosher Says: 

March 9th, 2010 at 5:46 am

32.

This is great.

Clear Climate Code » Blog Archive » The 1990s station dropout does not have a warmi... Page 12 of 16

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Can you guys either post the data tables or calculate 

trend lines for both cases.

drj Says: 

March 9th, 2010 at 8:03 am

33.

@Steven: secret fact about Google charts: the data is in the URL for the 

image. Right click on the graph and select “Copy Image Address” (or 

whatever is equivalent in your browser), then paste that into a 

document:

http://chart.apis.google.com/chart?cht=lc&chds=-

100,100&chtt=Global+Temperature+Anomaly|Land+Stations&chdl=post

-cutoff|pre-cutoff&chdlp=t&chd=t:9,-7,27,9,15,1,5,-32,-13,22,-9,-29,

-33,-28,-15,-16,-5,-1,-14,-21,1,1,-21,-29,-36,-25,-5,-32,-25,-26,-

14,-19,-29,-23,1,3,-12,-37,-27,-8,-13,6,-10,-13,-11,-14,6,-9,-2,-

23,-1,3,1,-11,2,-6,6,16,21,-1,9,7,9,5,12,-1,-2,10,-1,-9,-18,-3,2,11,-

8,-8,-17,9,11,7,1,11,5,2,-24,-17,-9,-2,-13,0,4,-9,-4,19,-6,-1,-

21,16,6,13,26,38,7,33,13,11,17,32,41,28,48,43,12,18,31,45,37,39,70,45,41,56,68,65,58,77,66,73,55,73,

-999%7C-25,-9,-14,-17,-55,-26,-37,-64,-41,-6,-41,-72,-55,-60,-

65,-54,-53,-22,-14,-32,-9,-9,-33,-42,-48,-35,-21,-49,-43,-41,-28,

-35,-28,-28,0,11,-27,-65,-36,-9,-19,-12,-13,-16,-16,-19,3,-6,2,-

23,-3,2,5,-14,5,-10,0,9,12,2,20,16,14,2,11,2,2,12,-4,-5,-9,-2,6,13,-

7,-8,-27,4,13,6,1,8,5,6,-28,-12,-4,-3,-5,10,9,-21,-12,16,-14,0,-

19,19,6,13,25,35,9,37,3,18,22,48,46,28,54,46,-999,-999,-999,-999,-

999,-999,-999,-999,-999,-999,-999,-999,-999,-999,-999,-999,-

999,-999,-999&chxt=x,y,r&chxl=0:%7C1880%7C%7C%7C%7C%7C%7C%

7C%7C%7C%7C1890%7C%7C%7C%7C%7C%7C%7C%7C%7C%7C1900%7C%

7C%7C%7C%7C%7C%7C%7C%7C%7C1910%7C%7C%7C%7C%7C%7C%7C%

7C%7C%7C1920%7C%7C%7C%7C%7C%7C%7C%7C%7C%7C1930%7C%7C%

7C%7C%7C%7C%7C%7C%7C%7C1940%7C%7C%7C%7C%7C%7C%7C%7C%

7C%7C1950%7C%7C%7C%7C%7C%7C%7C%7C%7C%7C1960%7C%7C%7C%

7C%7C%7C%7C%7C%7C%7C1970%7C%7C%7C%7C%7C%7C%7C%7C%7C%

7C1980%7C%7C%7C%7C%7C%7C%7C%7C%7C%7C1990%7C%7C%7C%7C%

7C%7C%7C%7C%7C%7C2000%7C%7C%7C%7C%7C%7C%7C%7C%7C%

7C2010%7C1:%7C%7C-0.5%7C+0.0%7C+0.5%7C%7C2:%7C%7C-0.5%

7C+0.0%7C+0.5%7C&chco=ff0000,0000ff&chs=440×330

See that list of mostly 2 digit numbers separated by commas? That’s the 

two data series (separated by %7C in the middle). The numbers are the 

actual anomalies in centikelvin (or 0.01 °C if you prefer). -999 is “no 

data”.

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This is true for most (all?) of the charts I’ve prepared for this blog. 

They’re made with Clear Climate Code’s vischeck.py tool.

drj Says: 

March 9th, 2010 at 8:08 am

34.

Trend calculation was always on the todo list; now I’ve created Issue 49

so that we have a permanent reminder.

drj Says: 

March 12th, 2010 at 7:45 am

35.

@Steven: Trends calculated, updated chart in a newer blog post

Dane CRU – średnie globalne anomalie temperatury | Prognozy numeryczne 

GFS/WRF Says: 

March 18th, 2010 at 6:23 pm

36.

[...] przypomnieć, Ŝe chłopaki z ccc-gisstemp potwierdzają dokładnie to 

samo w stosunku do analizy GISS. Wygląda więc na to, Ŝe problem ów 

wylągł się jedynie w głowach [...]

Scholars and Rogues » Climategate accusations shrivel under the glare of 

multiple investigations Says: 

April 19th, 2010 at 11:20 am

37.

[...] that better statistical methods would have changed the results – 

NASA, NCDC, and now multiple different amateur reconstructions have 

all replicated the basic results of CRU using the same raw data CRU [...]

» Af hverju eru færri veðurstöðvar og hver eru áhrif þess? Loftslag.is Says: 

May 16th, 2010 at 5:20 pm

38.

[...] greining var einnig gerð af Clear Climate Code, sem bar einnig 

saman hitastigsgögn fyrir stöðvarnar sem duttu út og þær sem haldið 

var [...]

D’Aleo at Heartland: An Apple a Day « The Whiteboard Says: 

May 25th, 2010 at 4:40 am

39.

[...] Clear Climate Code, Feb. 26, 2010 compares GISTEMP type 

calculations of global surface temperature anomalies based on the “full” 

and “cut-off” thermometer set. They find no major differences between 

the two traces. [...]

The Effect of Station “Dropout” on Gistemp | Peter O'Neill's Blog Says: 

June 25th, 2010 at 3:01 am

40.

Clear Climate Code » Blog Archive » The 1990s station dropout does not have a warmi... Page 14 of 16

http://clearclimatecode.org/the-1990s-station-dropout-does-not-have-a-warming-effect/ 7/29/2010
[...] results have been published recently at Clear Climate Code and by 

Tamino at “Open Mind”. This post provides further detail of the effect at 

[...]

Prawdziwe „Climategate” | Prognozy numeryczne GFS/WRF Says: 

July 18th, 2010 at 6:42 pm

41.

[...] kompletnie się mylili. Więcej na ten temat tutaj. Na stronie projektu 

ccc-gistemp takŜe moŜna znaleźć dowody, Ŝe skasowanie znacznej 

ilości stacji nie miało Ŝadnego wpływu na obserwowane trendy. [...]

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Clear Climate Code » Blog Archive » The 1990s station dropout does not have a warmi... Page 16 of 16

http://clearclimatecode.org/the-1990s-station-dropout-does-not-have-a-warming-effect/ 7/29/2010