Temperature averages of continuously reporting stations from the GISS dataset
Guest post by Michael Palmer, University of Waterloo, Canada
Abstract
The GISS dataset includes more than 600 stations within the U.S. that have been
in operation continuously throughout the 20th century. This brief report looks at
the average temperatures reported by those stations. The unadjusted data of both
rural and non-rural stations show a virtually flat trend across the century.
The Goddard Institute for Space Studies provides a surface temperature data set that
covers the entire globe, but for long periods of time contains mostly U.S. stations. For
each station, monthly temperature averages are tabulated, in both raw and adjusted
versions.
One problem with the calculation of long term averages from such data is the occurrence of discontinuities; most station records contain one or more gaps of one or more months. Such gaps could be due to anything from the clerk in charge being a quarter drunkard to instrument failure and replacement or relocation. At least in some examples, such discontinuities have given rise to “adjustments” that introduced spurious trends into the time series where none existed before.
1 Method: Calculation of yearly average temperatures
In this report, I used a very simple procedure to calculate yearly averages from raw
GISS monthly averages that deals with gaps without making any assumptions or adjustments.
Suppose we have 4 stations, A, B, C and D. Each station covers 4 time points, without
gaps:
In this case, we can obviously calculate the average temperatures as:
A more roundabout, but equivalent scheme for the calculation of T1 would be:
With a complete time series, this scheme offers no advantage over the first one. However, it can be applied quite naturally in the case of missing data points. Suppose now we have an incomplete data series, such as:
…where a dash denotes a missing data point. In this case, we can estimate the average temperatures as follows:
The upshot of this is that missing monthly Δtemperature values are simply dropped and replaced by the average (Δtemperature) from the other stations.
One advantage that may not be immediately obvious is that this scheme also removes
systematic errors due to change of instrument or instrument siting that may have occurred concomitantly with a data gap.
Suppose, for example, that data point B1 went missing because the instrument in station B broke down and was replaced, and that the calibration of the new instrument was offset by 1 degree relative to the old one. Since B2 is never compared to B0, this offset will not affect the calculation of the average temperature. Of course, spurious jumps not associated with gaps in the time series will not be eliminated.
In all following graphs, the temperature anomaly was calculated from unadjusted
GISS monthly averages according to the scheme just described. The code is written in
Python and is available upon request.
2 Temperature trends for all stations in GISS
The temperature trends for rural and non-rural US stations in GISS are shown in Figure
1.
This figure resembles other renderings of the same raw dataset. The most notable
feature in this graph is not in the temperature but in the station count. Both to the
left of 1900 and to the right of 2000 there is a steep drop in the number of available
stations. While this seems quite understandable before 1900, the even steeper drop
after 2000 seems peculiar.
If we simply lop off these two time periods, we obtain the trends shown in Figure
2.
The upward slope of the average temperature is reduced; this reduction is more
pronounced with non-rural stations, and the remaining difference between rural and
non-rural stations is negligible.
3 Continuously reporting stations
There are several examples of long-running temperature records that fail to show any
substantial long-term warming signal; examples are the Central England Temperature record and the one from Hohenpeissenberg, Bavaria. It therefore seemed of interest to look for long-running US stations in the GISS dataset. Here, I selected for stations that had continuously reported at least one monthly average value (but usually many more) for each year between 1900 and 2000. This criterion yielded 335 rural stations and 278 non-rural ones.
The temperature trends of these stations are shown in Figure 3.
While the sequence and the amplitudes of upward and downward peaks are closely similar to those seen in Figure 2, the trends for both rural and non-rural stations are virtually zero. Therefore, the average temperature anomaly reported by long-running stations in the GISS dataset does not show any evidence of long-term warming.
Figure 3 also shows the average monthly data point coverage, which is above 90%
for all but the first few years. The less than 10% of all raw data points that are missing
are unlikely to have a major impact on the calculated temperature trend.
4 Discussion
The number of US stations in the GISS dataset is high and reasonably stable during the 20th century. In the 21st century, the number of stations has dropped precipitously. In particular, rural stations have almost entirely been weeded out, to the point that the GISS dataset no longer seems to offer a valid basis for comparison of the present to the past. If we confine the calculation of average temperatures to the 20th century, there remains an upward trend of approximately 0.35 degrees.
Interestingly, this trend is virtually the same with rural and non-rural stations.
The slight upward temperature trend observed in the average temperature of all
stations disappears entirely if the input data is restricted to long-running stations only, that is those stations that have reported monthly averages for at least one month in every year from 1900 to 2000. This discrepancy remains to be explained.
While the long-running stations represent a minority of all stations, they would
seem most likely to have been looked after with consistent quality. The fact that their
average temperature trend runs lower than the overall average and shows no net warming in the 20th century should therefore not be dismissed out of hand.
Disclaimer
I am not a climate scientist and claim no expertise relevant to this subject other than
basic arithmetics. In case I have overlooked equivalent previous work, this is due to my ignorance of the field, is not deliberate and will be amended upon request.
GT? Work it out? What FUD would that be?
😉
barry says: October 25, 2011 at 3:48 pm
Thanks. Appreciated. Looks like a lot of thought went into that post of yours. I shall try to assimilate it all and reply here asap but cannot do so right away. Or if this thread fails you can email me.
barry says: October 25, 2011 at 3:48 pm
I did not express myself adequately here, I apologize for that. But, as I said on my UHI page, the problem is that even rural areas with the lowest populations can have UHI. Ilarionov showed that statistically, the most-rural areas have the greatest temperature increase – even though their actual temperatures may well be lower than nearby urban areas. This disparity in delta T has to be UHI, and it shows me why even Zeke’s work is insufficient to compensate UHI in a way I can trust.
If you had read my page carefully you would have seen Ilarionov is a scientist whose work deserves checking, not least because it has the “statistical analysis of a large number of stations” that you wrongly claim my page lacks – and it’s easy to follow.
I lack the skill to determine if Michael Palmer’s methodology (post-selection) is sound, and wouldn’t try to speak to that. I did notice Glenn Tamblyn’s comments (who does have the skill), which articulated strong reservations about Michael’s number crunching. Michael has not given a substantive reply to that. Is there a reason why I should unskeptically accept Michael’s results?
Of course you should not uncritically accept Michael Palmer. I did not. It took me a long time to find answers to all Skeptical Science’s “answers to skeptics” but I did otherwise I would not be a skeptic myself now. I’m not going to waste my time repeating my story here. Relevant here, however – I realized the importance of a few trustworthy individual longterm records over numbers – in fact, over almost all the other records, and over the use of true “number crunching” that turns several stations’ results into an area soup. I have written up several web pages referring to such records, two of which were published here (“Circling the Arctic” and “Circling Yamal”). You could have guessed something like this, from my very first comment here, thanking Michael Palmer.
I doubt that you lack the skill to check Michael, if you were to apply yourself. You seem bright enough. I am not going to wade into Glen Tamblyn at all, seeing as he posted so much that did not even begin to address Michael’s work. I am also skeptical of your claims that Glenn has the skill, or that Michael has not given a substantive reply. But the above answers you enough IMO and any more checking seems like a waste of time.
I hope this clears up the misunderstanding due to my bad use of words, and also shows that I did pay attention, as I claimed – and that you need to pay closer attention to my work. Thanks for your attention and concern, I appreciate it.
@Smokey, again with the lists of scientists that reject ACC. 30,000 out of millions is a tiny fraction of scientists and engineers, most of which have expertise in fields completely unrelated to the climate. None of this nullifies that polls indicate wide acceptance of ACC. Hundreds of scientists reject evolution as well
http://www.discovery.org/scripts/viewDB/filesDB-download.php?command=download&id=660
that doesn’t negate polls showing ~95% support.
I want to make sure I have your position correct. You think that most scientists reject ACC, and despite this, in a massive, unprecedented conspiracy, every major scientific organization, country, etc. has been co-opted by a small number of scientists and politicians wanting to push GHG limits/taxes in a desire to, what? Protect their research funding? Control people?
Smokey, I’m not sure why you’re posting misleading temperature and sea level data when you’ve already admitted that you accept warming, and that humans are causing at least some of it but I’ll bite. First, these are single figures, with no context, posting on “skeptic” blogs. These are probably part of a study with descriptive text but that information isn’t given. The first image shows increasing sea levels except for the past year or two (a few years in one model). The second shows wildly oscillating atmospheric temperatures over a very short time scale. Here is similar data over a longer timeframe.
http://upload.wikimedia.org/wikipedia/commons/7/7e/Satellite_Temperatures.png
Given the rate of temperature increase compared to yearly fluctuations you wouldn’t expect an increase every year. 2000-2010 was warmer than 1990-2000 and I’ll be very surprised if 2010-2020 isn’t warmer still.
“The fact is that every claim of the climate alarmists evaporates under scrutiny.” This seems to be your only, real belief. You claim that you believe CAGW except for the “C”. This wouldn’t be such an unreasonable position if you (all) didn’t show such a propensity to attack any data showing any part of CAGW. Your conflation of alarmists with scientists is concerning as well. Scientists aren’t saying it will definitely be catastrophic. More like, it’s definitely happening, and will probably be bad, and hey, maybe we should do something about it just in case while we figure things out a little better. Yet you attack any climate research that is produced.
Brian says:
“…again with the lists of scientists that reject ACC. 30,000 out of millions is a tiny fraction of scientists and engineers, most of which have expertise in fields completely unrelated to the climate. None of this nullifies that polls indicate wide acceptance of ACC.”
Cognitive dissonance is generally incurable, and Brian has it bad. He confuses 30 thousand scientists out of millions, when the correct way to view the numbers is a comparison of those 30,000+ skeptical scientists with the number of climate alarmists who signed their various counter petitions. Last I heard their total was less than 1,500. And that’s for all their contrary petitions.
Skeptics outnumber alarmists by about twenty to one in that legitimate comparison, and there is no reason to believe the general public is much different. Gallup routinely extrapolates 3% or less of a sample to the entire population. And more often than not, Gallup is right. Brian is only fooling himself if he believes everyone thinks like he does.
Smokey, don’t waist any more of your time. Wrestling with a pig in the mud is useless. Eventually you discover the pig just likes the mud.
Between the two of us he has received 15 indisputable sources of information that he has refused to verify. If he wants to keep watching the Gorathon videos let him. From now on he isn’t worth my time trying to help or to even respond to.
Lucy,
thanks for the thoughtful reply. I will read more on your site. The link to Ilarionov didn’t work for me, but to go from your comment:
That assumption may not be warranted. For example, airports, which one would assume should definitely have a UHI effect, actually trend lower than total stations, or than non-airport stations. Here, there is no murkiness regarding classification (an airport is an airport). Ilarionov considers only Russian data, so perhaps there is something going on seasonally or whatever, that somehow cools the urban record – there are instances of that occurring in cities, with station moves from built-up areas to parks. Nothing conclusive offered here, of course, but I think it would be a mistake to presume a particular cause for this disparity. More investigation is needed*.
However, on your page you appear to be presenting the opposite notion from Ilarionov – that the most-rural trends are lower than urban.
* I guess I’d need to see his documented Heartland presentation to sort this out. I’ll see if I can find it after work today (if you don’t happen to drop a better link in the interim :-).
barry says: October 26, 2011 at 10:49 pm
Lucy, thanks for the thoughtful reply…
And thanks for yours. My web page Heartland link has gone dead. Removed now. The two U-tube links given subsequently work. And bear in mind that Spencer also notes UHI effects at very low population density (same page). All this bears out the notion of Watts’ original investigations IMHO. If I think of a weather station in the Arctic, for instance, I feel one is likely to contend with at least these changes:
Station closer to habitation (because of electrical wiring to instruments)
Runways expanded, cleared more, used more
More local buildings
Brian says:
October 25, 2011 at 12:30 pm
Which one doesn’t? The organizations are made up of the people in the organization.
_______________________________
Jeff D says:
October 25, 2011 at 1:04 pm
…..As for the groups; ask them for the survey they sent to the members for their stance on CAGW. I took the time to ask two groups. Seems they didn’t poll their members but took a vote of the board for a determination. A Noble prize winner removed himself from one of these groups for just this reason. American Scientific Association I think, Again there was an article posted here on WUWT following just this…..
______________________________________
I belonged to two scientific organizations and quit after 30 years+ membership for just that reason. I got sick and tired of the organizations taking a “Politically Correct” stance instead of sticking to science
I suggest you read about one of the organizations I quit here:
American Chemical Society members revolting against their editor for pro AGW views
http://wattsupwiththat.com/2009/07/30/american-chemical-society-members-revolting-against-their-editor-for-pro-agw-views/
HenryP says:
October 25, 2011 at 8:18 am
Henry@Garret
…. (on the interpretation of the greenhouse effect)
…..If you want a bit more understanding of the problem, you can go here:
http://www.letterdash.com/HenryP/the-greenhouse-effect-and-the-principle-of-re-radiation-11-Aug-2011
(I have tried to keep it as simple as possible, and have asked for comments from my peers here if there is anything wrong with this explanation)
Obviously, this being the case, it follows that, if you say that the extra warming we experience is not natural, we must assume that the flow of warmth from the sun is or was constant – in which case maxima should not be rising. If you say that the warming is due to an increased greenhouse effect it should be minimum temperatures that are rising…..
____________________________________
If you take what you are saying to the logical conclusion then the greenhouse effect does not cause “warming” it causes a moderating of the extremes in the night/day temperature cycle. The real life demonstration of course is seen in the deserts where the greenhouse gas H2O is missing and the day time/night time temperature swings are extreme compared to a humid day/night at the same latitude.
The practical applications are the sprinklers in Florida orchards used to protect fragile fruit trees.
A good explanation: http://edis.ifas.ufl.edu/ch182
Albert Einstein said ” No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”
But it seems a lots of money, propaganda and political power sure can keep a dead theory walking!
Brian says:
October 25, 2011 at 8:53 am
@Smokey et al
……Scientists think AGW will probably be bad, partially because we’ve built society around how the climate is right now. Is it likely to be catastrophic? No. The Gore/Greenpeace “alarmists” as you call them are out of step with the science on this. The point is that if AGW is “probably” bad and even “possibly” terrible, it makes sense to start taking modest steps to address it, using best-estimate cost-benefit analyses. If 10 years from now we realize it’s not warming as fast as we thought, it’s a lot harder to cut back on GHG emissions than we thought and mitigation is likely to be cheaper than avoidance, fine. Our policies can evolve. Scientific knowledge evolves and our opinions and actions should be based on the best available knowledge at the time…….
______________
Fine Brian then start actively promoting Nuclear Power (Thorium) as Anthony has. http://wattsupwiththat.com/2011/03/30/anti-nuclear-power-hysteria-and-it%E2%80%99s-significant-contribution-to-global-warming/
That is a reasonable solution that does not involve Genocide by Eucaluptus tree:
http://wattsupwiththat.com/2011/09/25/they-had-to-burn-the-village-to-save-it-from-global-warming/
http://wattsupwiththat.com/2011/09/25/they-had-to-burn-the-village-to-save-it-from-global-warming/#comment-754959
http://wattsupwiththat.com/2011/10/13/borlaug-2-0/#comment-767559
Global Land Grab: http://www.inthesetimes.com/article/11784/global_land_grab/
World Bank Links: http://web.worldbank.org/WBSITE/EXTERNAL/NEWS/0,,contentMDK:22785667~pagePK:34370~piPK:34424~theSitePK:4607,00.html
I believe in practicing what I preach so I am staring at a nuclear plant as I type….
Gail Combs says:
http://www.letterdash.com/HenryP/the-greenhouse-effect-and-the-principle-of-re-radiation-11-Aug-2011
If you take what you are saying to the logical conclusion then the greenhouse effect does not cause “warming” it causes a moderating of the extremes in the night/day temperature cycle. The real life demonstration of course is seen in the deserts where the greenhouse gas H2O is missing and the day time/night time temperature swings are extreme compared to a humid day/night at the same latitude.
Henry@Gail
Yes, I am sure you are right. I am not even a 100% sure if the net effect of more humidity in the air causes warming (by deflecting earth light) rather than cooling (by deflecting IR light from the sun) but that it causes a balancing act between extremes is for certain. In fact, I believe that is why life exists at all.
http://www.letterdash.com/HenryP/what-was-that-what-henry-said
Brian says:
October 25, 2011 at 3:41 pm
…..If you’re willing to admit that the earth is warming, and humans are causing it, we can have a more productive discussion about the likelihood that it will be bad, and what to do about it. But I doubt you’ll admit there’s any chance you’re wrong…..
___________________________________________-
Why the heck would we admit we are “WRONG” when the science is far from settled???
900+ Peer-Reviewed Papers Supporting Skeptic Arguments Against ACC/AGW Alarm
More to the point why would we agree to the World Bank’s plans to rape the poor and middle class???
It completely flabbergasts me that people who clamor about how we must DO SOMETHING about CAGW to save humanity completely MISS WHO is PROFITING from CAGW and the very real fact they are condemning children under the age of 5 to horrible deaths.
This is NOT now substantiated in fact.
The so-called Danish text, a secret draft agreement … hands effective control of climate change finance to the World Bank…
http://web.worldbank.org/WBSITE/EXTERNAL/NEWS/0,,contentMDK:22785667~pagePK:34370~piPK:34424~theSitePK:4607,00.html
http://wattsupwiththat.com/2011/09/25/they-had-to-burn-the-village-to-save-it-from-global-warming/
http://www.bread.org/hunger/global/
http://www.thirdworldtraveler.com/IMF_WB/Budhoo_50YIE.html
http://www.whirledbank.org/development/sap.html
http://www.whirledbank.org/development/debt.html
Global Land Grab: http://www.inthesetimes.com/article/11784/global_land_grab/
A Quickie on the 2008 food riots that shows just how ruthless these people are in their quest for money and also shows the l: http://wattsupwiththat.com/2011/10/13/borlaug-2-0/#comment-767575ong term planning.
[snip. Enough with the politics. ~dbs, mod.]
Been having a disscussion with a warmist and used this post as evidence of lack of century scale warming. Apparently he’s been learning a few things from our exchanges and toss back at me an argument I have used offen. Out of the 613 station used in the graph. How many of them passed the Surfacestation review for siting?