A guest post by John Goetz
In my post December 1986, I presented a histogram showing the GISS estimate of December 1986 minus the actual for GHCN stations in Europe and Russia. As noted, GISS under-estimated December 1986 for this region by a greater than 2 to 1 margin. The result was, when GISS combined multiple records for a single station, the stations with a cold estimate for December 1986 had their records artificially cooled pre-1987. By cooling the older record and leaving the current record unchanged, an enhanced warming trend was introduced.
I promised I would show other regions of the world in future posts. Therefore, in this post I present Africa, which essentially shows polar-opposite results from Europe / Russia.
In Africa, GISS tends to over-estimate December 1986 when combining records. Because the temperature is over-estimated, older records must be warmed slightly before they are combined with the present record. By introducing artificial warming in a past record, the overall trend through the present is cooled.
Following is a histogram showing the GISS estimate of December 1986 minus the actual for GHCN stations in Africa.
The implication is that the GISS algorithm introduces a cooling trend to most African records.
As can be seen in the next plot, however, the number of stations reporting temperature data in Africa drops off rather sharply before 1950. This means any warming of past records likely does not go very far back in time.
We need to peek backwards some and see how many of the “warmed” station records actually exist before 1950:
| 1950 | 1940 | 1930 | 1920 | |
| Warmed | 50 | 10 | 8 | 5 |
| Cooled | 31 | 13 | 13 | 10 |
| No Change | 52 | 22 | 19 | 15 |
As can be seen from the table above, prior to 1950 the “cooled” stations tend to outnumber the “warmed” stations. In other words, from roughly 1950 to 1986, GISS artificially warms the African records, and prior to 1950 it artificially cools the records. Granted, we are not talking about a lot of stations here, but it does give one whiplash from all of the double-takes.
As was pointed out in several comments to December 1986, the average bias for that month, while negative, was not particularly large. Furthermore, the value would end up being divided by 36 or 48 in order to yield the adjustment amount. See here and here.
The same is of course true of Africa. The implication in both cases is that the net adjustment ends up being so small that we won’t see it at the global or perhaps even zonal level. This might indeed be true. Whether the trend is enhanced or not does not necessarily mean the trend is not there. At the macroscopic level the adjustment may not matter at all.
Nevertheless, I find it rather amusing / interesting / ironic that as I go back in time and look at the average bias adjustment of African stations, the cooled stations not only outnumber the warmed stations, but they far outweigh them when averaging the adjustment. This comes in spite of the fact that most of the records get the warming bias.
Here is what I mean:
“As can be seen in the next plot, however, the number of stations reporting temperature data in Africa drops off rather sharply before 1950. This means any warming of past records likely does not go very far back in time.”
Did you apply the same analysis when you looked at the Europe/Russia records? I’m wondering why you pick up this point here when considering a cooling trend but not, apparently, when considering a warming trend?
Reply: Yes, I did last year and again this year, but I have not yet tied those loose ends into this latest thread. It is on my to do list. Here is a teaser graphic I generated last year and posted on CA.
As for this post, I happened to notice the bias plot for Africa as I was writing the above post and looking back through older analyses. I thought “this is odd”, which caused me to look more closely, and ultimately changed the conclusion I was originally drawing (and planning to post).
On CA, the contention was that GISS was cooling the past (esp. the 1930s). Steve Goddard also pointed out that GISS “adjusted” the recent ten-year slope by six degrees (angle, not temperature!).
This all seems in line with that. I want to see the raw data and then ech adjustment shown and explained. The way NOAA did it for USHCN1.
Unfortunately, since that explanation became one of the most quoted passages (and graphs) by skeptics, NOAA has (most wisely) stopped providing the information in accessible form!
So far as those “adjustments” go, “Everything that is suppoed to be UP is DOWN! And everything that is supposed to be DOWN is UP!” to quote Al Gore.
What’s this I hear about a new sunspot cluster. Is it real? Or am I misinformed? (I can’t find it on the web.)
” Evan Jones (11:44:35) :
What’s this I hear about a new sunspot cluster. Is it real? Or am I misinformed? (I can’t find it on the web.)”
It’s here
http://sidc.oma.be/LatestSWData/LatestSWData.php
It has a Catania number – the observer at Catania saw it and drew it this morning
http://web.ct.astro.it/sun/draw.jpg
but not yet a NOAA number.
It’s so tiny that the observers at Mt. Wilson
http://www.astro.ucla.edu/~obs/cur_drw.html
Locarno and Uccle among others, did not see it.
http://www.specola.ch/e/drawings.html
http://sidc.oma.be/images/last_ORBdrawing.jpg
In the magnetograms
http://gong.nso.edu/Daily_Images/
it has a Cycle 24 signature (negative (black) polarity leading in the northern hemisphere), and would be consistent with Cycle 24 producing none or few spots, and then only very weak and short-lived.
Also very important about this spot is the low solar latitude (about 15 degrees north).
That’s unusually low for early, new cycle spots.
From solarcycle24:
“My understanding is latitude trumps polarity, which would make this sc23. But first it has to become a spot we can see. Plage areas don’t count. And it has to exist as a spot for some minimum time.”
@John-X (12:44:15) :
Also very important about this spot is the low solar latitude (about 15 degrees north).
That’s unusually low for early, new cycle spots.
Is the polarity certain to be SC24 type? I was also puzzled by the low latitude and assumed it was an SC23 group, which would be interesting of course.
Either way it seems odd.
“a gargantuan house of cards rested on models, assumptions, and values that were, for the most part, baseless. It was hard for the man on the street to know this, of course, because thoroughly-conflicted insiders, clueless academics, corrupt politicians, toothless regulators and various industry shills were running around claiming that they knew what was going on” . As it happens, he was writing about Wall St, but his remarks might be more widely applicable, don’t you think?
John, the task of epic proportions and a significant result.
… .. it artificially cools the records… .. (U$ 30 billion)
Leif Svalgaard …. Please HELP …..
Evan Jones…good question (about the whales; we talk later. civility above all.)
John Goetz,
Thanks for your response to my question above. You’ll understand, I’m sure, that I’m trying to get an idea of what net effect any of this may have had on the GISS record. It’s interesting to consider the effects (both cooling trend and warming trend) at the micro level, but it remains somewhat academic without knowing whether or not this has had a significant effect upon the record as a whole.
Personally, I am not alarmed by the fact that record blending will give rise to some systemic fudging. I would be alarmed by any evidence of human bias in such a process, or evidence of the fact that such a process undermines the effective reliability of the ‘end product’ record. Without some evidence of the former, or some figures to judge the latter, this seems to me to be interesting but (currently) inconsequential. Perhaps you’re heading towards some figures to quantify net effect, at which point it will be very interesting to look at your conclusions.
Re: Evan Jones (10:56:42)
Evan,
You said, “The way NOAA did it for USHCN1.” I’m a newcomer to CA and this blog. Can you please direct me to the archives here or at CA (or other sources) that contain NCDC’s explanation of their adjustments of USHCN surface station data sets?
Thanks
Evan Jones…good question (about the whales; we talk later. civility above all.)
To be clear, whales are very intelligent, and thus I regard them as especially worthy of protection, regardless of whether they are endangered or not.
It is interesting to note the juxtaposition of the current “War on Terror”/oil put side-by-side with the 1830-1860 “War on Piracy”/whale oil.
hmccard: Will do.
You are gonna just–love–this!
http://www.ncdc.noaa.gov/oa/climate/research/ushcn/ushcn.html
http://www.ncdc.noaa.gov/img/climate/research/ushcn/ts.ushcn_anom25_diffs_pg.gif
<iI would be alarmed by any evidence of human bias in such a process, or evidence of the fact that such a process undermines the effective reliability of the ‘end product’ record.
I don’t know what you mean by ‘human bias’. All bias results from humans. ‘Noise’ is used to describe non-human sources of error in measurements. There is definitely bias here.
And that bias will definitely affect the ‘end product’ record. However, John cannot say by how much. So all we can say we with certainty is that some of the reported temperature trend is due to human bias.
hmccard: Just posted the links. (Hope they don’t get caught in the spam filter.)
Reply: They did–I sealed up my nostrils, closed my eyes, reached in, and dug them out.~charles the moderator
Philip_B, let me answer for Steven Talbot. I believe he was referring to intentional versus unintentional bias.
Potential unintentional biases which in some way can all be considered human biases, but not what he was referring to:
Observation bias
Instrumental bias
Improper analytic procedure bias (what this post is about)
Jeez: Thanks.
And thanks to JX/TT for the sunspot info.
There can also be unconscious bias where you’re actively creating a bias because it agrees with your preconceptions. So you wind up correcting for biases that don’t support your preconceptions while ignoring those that do. It’s intentional but not consciously so.
Yeah, and it’s called observation bias.
Evan,
From your refs I got this:
http://www.ncdc.noaa.gov/img/climate/research/ushcn/mean2.5X3.5_pg.gif
Looks like the different methodologies at most any given time are greater than the supposed temp increase in the last 100 years! How do we really know that global mean temp has increased at all? Not that I think there has been no increase.
jeez – thanks 🙂
In order to introduce any intentional bias or observational bias to this, it seems to me that the scientist(s) would have had to have calculated the effects of alternative methods of blending the records, and then chosen the one which best favoured the intent, or was in best accord with their observational bias. I find that quite implausible, and am more inclined to think that they simply chose a method which may have arbitrarily thrown up some systemic error.
At the moment we cannot say whether bias of any kind is either positive or negative in terms of global trend. It will be interesting to see whether a time comes when we can, and then whether it is of any consequence.
de nada
Steven Talbot,
I wholeheartedly reject the idea that there is any form of intentional bias in the results or most of the records. I think there might be some intentional bias in some of the records, but that is a topic for a future post as I continue gathering evidence.
I use postings like this to do nothing more than think out loud about some “micro-level” step in a much larger process. I do keep the broader process in the back of my mind, but right now it is too hard for me to put my arms around the full set of implications.
I posted the following comment on CA in response to someone asking if the adjustments “CAN”T be anything but insignificant”. It is essentially an outline of the questions I ask myself and periodically find time to investigate:
I am not yet convinced of the significance one way or the other.
1. The distribution of stations worldwide is nowhere near uniform. This is true now and back through the historical record. The United States has far more representation in the record than any other country or region on the planet, yet occupies only about 3% of the surface, as we are sometimes gently reminded. The gridded temperatures covering the US are going to therefore be more accurate than elsewhere. How much more is not yet known to me.
2. The number of stations participating in the effort to measure global temperature was greatest from roughly 1950 to 1990. Prior to 1950 the number grew from very few stations in 1880 to a moderate number in the late 1940s, before jumping dramatically. Since 1990 the number has dropped dramatically, such that now the number of stations participating is roughly equal to that in the very early part of the 1900s. There’s progress for you! Of course, that does not mean the same few stations reporting now were reporting in 1900. Some have come and some have gone.
3. Even the few stations that have been reporting that long have gone through changes that affect the fidelity of their records. We have seen that the Burlington, Vermont station has not always been located at their international airport because, well, airplanes did not exist when the station first began reporting. Like a present-day yuppie, the station migrated to the burbs over time, having originated in downtown close to the lake. Along the way it spent time in a couple back yards, on a city roof, and at the local university. Hopefully not partying.
So, we start with rather mediocre spatial and temporal representation. To that we add:
4. Of the records we do have, most are missing a number of monthly data points – some more than others. There are many reasons data might be missing, but one thing we have learned is that GHCN will drop an entire month’s worth of data if even one day is missing or suspicious. This happens over and over and is not a rare occurrence. This missing day or days could be estimated using a variety of techniques, or better yet, some of the days can be recovered if someone actually looked at the record and spotted the typical transcription error. You know, when June 10 is 24C and June 12 is 25C, but June 11 is -23C. That type of error will result in the entire month being discarded. Whaddya thing the real June 11 temperature was???
5. So rather than fixing a transcription error here or there or estimating the missing day or two, GHCN drops the month and leaves it up to GISS to estimate the month. We have seen just how robust that estimation is. (Imagine for a second you are watching Lewis Black tell you this).
6. Now, GHCN very, very often passes along multiple records meant to represent a single station. Many times these records are consistent, indicating they are essentially pages from the same book. Sometimes they are not, which could mean they came from some other nearby location, were collected by a different piece of equipment – who knows. GISS says “what the heck, I don’t have a lot of records to begin with, why don’t I just splice these bad boys together and make one long record.”
You can imagine what might happen when two records from different books are spliced. You get sausage. But interestingly enough, as we have seen, even when they are from the same book you still get sausage, just a milder variety.
7. Keeping to the theme of not throwing away a good record no matter how crappy it looks after we’ve ground it up, we come to the point where we need to adjust urban stations because we know their temperature trends are artificially inflated by the urban heat island effect. So we find the rural stations that are within 500km, or wait, maybe sometimes 1000km (the distance from Indianapolis, IN to New York, NY), munge their trends together, and decide that MUST be the real trend of the urban station. So we go in and change the urban stations record so that its trend matches the munged trend, whipping the station back into line.
From that point comes the gridding part, which I have yet to explore in my spare time. I’ve also not bothered to mention the other machinations that go on with the record, such as the TOBS adjustment and infilling. I’ve ignored mentioning how the temperature is collected and whether or not station standards are consistently met or not met.
Nevertheless, from this we have pronouncements that the earth is 0.7 degrees warmer now than it was 100 years ago, and that Armageddon is upon us and we need to make some serious policy decisions based on the data. And equally robust simulations.
So no, I can’t conclude that the adjustments “CAN’T be anything but insignificant”. To me, what is done with the historical record is nothing more that putting out a fire with an ice pick.
John Goetz (18:43:02)
‘So no, I can’t conclude that the adjustments “CAN’T be anything but insignificant”. To me, what is done with the historical record is nothing’….
I think you ran out space.
Reply: Or your browser did, because I see it all in my browser.
John Goetz: It was better than the post: clear.
http://www.surfacestations.org : We know what is inside those boxes. (called meteorological stations).
Armageddon: hmmmmm
Evan?
The dinosaurs were extinct:
a – Because an asteroid (meteor or comet) collided with Earth?
b – Because they did not know what was an asteroid (meteor or comet)?