Can you spot the GIStemp baseline? How about the HadCRUT baseline? (Yes, it’s that cold plunge part). But recently the “inconvenient” hot lead in to that plunge as slowly evaporated from the historical record. One is left to ponder “Why?”…
I read things. It’s what I do. “Input, must have input!” (from “Number 5” in the movie “Short Circuit”.)
So as I’m having my morning cup of “hello world” or my evening cup of “Now I lay me down”; I’m usually reading something. Last night I was reading a link that I’d opened some days past. (I think it was from “tips & notes” at WUWT, where I often see interesting hints, but don’t have the time to follow them up mid-day; so just click to open a tab for ‘later’… that sometimes ends up “a few days later” after I’ve forgotten who deserves the h/t. I think I need a note pad to jot those things down… or it could be from a comment here some days past. At any rate, the contributions of others is appreciated.)
This article was about The Old Data. Prior to the time that money and fame caused AGW to become A Cause; back when folks just wanted to know what the temperature was. It’s an interesting article…
The top level / intro largely just recapitulates the first half of the first segment of the article, then has links to the other segments (including a repeat of the first segment bits). I’m putting the link here, but I would skip to the Segment 1 link as it will read more fluidly. The major difference is some bolding and where the table of contents is presented.
So I would just read these “Part One” to “Part Four” links directly.
It’s all “good stuff”.
Like what? How about some selected quotes?
Phil Jones, 1985, about the temperature decline after the 1930´ies:
“No satisfactory explanation for this cooling exists, and the cooling itself is perplexing because it is contrary to the trend expected from increasing atmospheric CO2 concentration. Changing Solar Activity and/or changes in explosive volcanic activity has been suggested as causes… but we suspect it may be an internal fluctuation possibly resulting from a change in North Atlantic deep water production rate.”
So, Jones said in 1985 that: “the cooling itself is perplexing” – but why not say so today? And why don’t we see a “perplexing” cooling after 1940 in the IPCC graphic today? And furthermore, back in the early 1980´ies Jones appears to accept data as is at least to such an extent that he is considering how nature has produced these “perplexing” cooling data – like a real scientist should.
I’m especially fond of that “internal fluctuations”…”from a change in North Atlantic deep water”. Gee, maybe the planet has cycles all on it’s own. Guess he’d not been “in church” long enough at that time and was still wondering about the status of the Apocrypha…
4) “Moving stations out of town to avoid UHI explains warming corrections”
Again, this is really Nonsense. Despite relocation of some temperature stations, UHI still induces far too much warming in temperature data in general world wide:
Thus: Any correction in connection with UHI should overall be towards colder temperature trends. If you make a warm correction due to stations moved out of town, you should make a much larger cold correction for the much larger UHI effect. The UHI is generally very much larger than the effect of relocating globally.
So it looks like Jones and friends DID believe in UHI back when they needed to do a “wrong way correction” to explain some coldening of the past, but now find it an inconvenient thing about the present…
5) “Temperature stations moved to higher altitude explains warming corrections”
Nonsense. If you place a station at a higher altitude, the temperature is likely to decrease and should be corrected. So we have a world wide trend during the 20´eth century where all countries starting in year 1900 independently of each other started to move their temperature stations up the hills?? I think any such altitude correction globally needs to be confirmed by some strong statistic data that shows that in general, temperature stations has been moved up in altitude. Anyone published on this subject? I would be surprised…
I find this one fascinating as my study of GHCN “by altitude” shows a profound movement to LOWER altitudes. Yet here they use the excuse that stations were being moved to higher altitudes as a reason to make “warming corrections”. Golly…
More on the GHCN series of odd artifacts can be found in the NCDC / GHCN Category:
Given that, I find it particularly of interest that today they argue that altitude changes do not matter while in the past they argued that they did matter….. “Heads I win tails you lose!” seems to be their mantra. The past can be such a cruel master… best to control it…
The whole article is full of little bits that need a bit of thinking about. Many fall into the category of “The excuse given is valid for A spot, but not ALL spots, yet applied to all.” For example:
(My comment would be, that a 5×5 grid in the tropics is many times bigger than a 5×5 grid in the Arctic, so even the good grid methods are not a “perfect” approach in my view. Obviously each fraction of the globe should have same area to have same weight…! )
The question of: “Does the grid spec over weight the arctic”?
There is an attempt at an “equal area” grid in the present GIStemp that may have mitigated some of this historical argument; but that just leaves me with this pondering:
GIStemp is a LAND temperature series. They “glue on” a Hadley Sea Surface Temp series as a completely OPTIONAL step, but it isn’t used in the bulk of their code, processes and prestidigitations prior to that last “glue it together” step. And there is a lot more land in Canada and Siberia than in Central America. So does the shape and distribution of the land itself introduce an inevitable bias?
Then on TOBS:
10) “The measuring time, TOBS, has changed, and it so happens, that this gave too warm temperatures earlier, we must add a warming to later data then”.
What we need here is a solid independent documentation, that all over the world in all countries rich and poor, they have actually synchronically shifted the Time of OBServation to slightly earlier to explain the world wide TOBS warming corrections. Remember, these temperature data was taken in 1930, 40, 50 , 60, 70 – in times when temperature data were just for trivial weather use. So why would poor countries prioritize new equipment etc? And if new machinery was introduced, howcome they did not set the machine to measure at the same time as they used to? Howcome there is a world wide trend that they just happen to set the machines to measure a little earlier?
Before accepting such coincidence – that just happens just yield another reason to add warm to data – I would like to see the world wide independent made graph of a still earlier TOBS in order to evaluate this apparently rather odd reason to reduce the 1930-70 decline in temperatures.
There seems to be a bit of misunderstanding of how TOBS works, that it’s not the time of day during which the data are measured, but the moving of a “max” from one day to the next based on when during the day you read and reset the min /max thermometer; but the point remains:
A TOBS adjustment is applied to all in synchrony when there is absolutely no reason to think that all CHANGED in sync. What justification is there for that? And for places like San Diego (where it’s substantially identical from day to day for weeks on end) what justification there? Would not TOBS adjustments need to be ‘custom made’ for each location?
Thats the kind of thought this article inspires. There is a lot more in the article, and I think I’ll be pondering bits of it for quite a while. It’s a long, detailed, but well thought out article.
The graph at the top of this page is a link to the graph in part two of the article. It shows a set of data that is rather well distributed over the globe. Better than GHCN IMHO.
Above: Angel and Korshovers radiosonde stations. Using Modern GISS std. Coverage radius of 1200 km, it becomes evident that most of the NH land area is in fact covered to some degree by the Angel and Korshover stations. These have been spread out to cover the Earth best possible.
The black areas – the areas not covered at all – are distributed very randomly over the whole Northern hemisphere, and thus, should these black areas have a temperature trend significant different from the green covered areas, then Angel and Korshovers data would be wrong. But it is likely, that black areas scattered and spread out on the Northern hemisphere just by coincidence should have a common trend significantly different from the rest of the Northern hemisphere? No, of course not, and therefore it is in fact not really a surprise that we see a good agreement between Jones 1982 and Angel and Korshover 1982.
The number of stations in Angel and korshover is just 43, but they are spread out evenly over the Northern hemisphere – and therefore useful.
So, as in many other cases, The Old Data checks and cross checks. It’s the modern monkey business that doesn’t add up. So the Inconvenient Past gets rewritten.
I have seen 2 explanations for adjusting the 1940-46 SST peak down:
1) during war, all over the world an night peoble dared not stand on their boats with a flash light when collecting the bucket of sea water. So all over the world SST collecters have had the same scare? Maybe a German bomber plane would appear in the south pacific? The Hudson Bay? Near the great barrier rief? Near Brasil? Alaska? Sure thing. As a consequence water was taken in by the machine inlet under water surface.
2) The material of the buckets where shifted simultaneously and the new material led to a different temperature inside the bucket.
A very interesting point. To what extent did folks in, for example, Argentine waters decide they would be attacked by their German friends? Do we really KNOW what the conversion time and areal coverage was?
However, the 1940´ies strong warm peak in ocean temperature data was not just a water temperature problem (SST). In fact, the warm peak of the marine air temperature (MAT) was even stronger than the sea surface water (SST) warm peak.
So the very idea, to focus on the water buckets when explaining the 1940´ies warm ocean temperature peak appears surprisingly wrong. Or perhaps people at sea started using buckets for air just around 1940?
Further discussed here: http://climateaudit.org/2005/06/19/19th-century-sst-adjustments/
So now I’ve got a few more “ToDos” on my “ToDo” list… ;-)
And there is more. So much more. There is a wonderful set of graphs of SST and some of Hansen’s land, all showing the same sort of Rewritten Past. If fear we need a new category of Scientist. The Data Archaeologist. Just to sort out this kind of mess.
We thus have a compare NH 1981 land stations vs. NH land stations 1986. I find the resemblance of the 81 and the 86 version convincing all the way up to 1963. – A superb match definitely showing my original Hansen 81 calculation to be useful (even though I had to use the temperatures from full tropic for the NH tropics).
The interesting lesson from this graph is, that suddenly around 1963 the newer 86 version is adjusted up compared to the 81 version, see the grey curve in the bottom of the graph.
What type of adjustment can explain this sudden significant divergence only starting in 1963?
One also gets fine “catches” like the early onset of “Lying with Color” by Hansen in this graph:
At first glance it would appear that most areas has warmed slightly in the very period of temperature decline after 1940??
Note that Hansen has chosen to make the yellowish colours start already at – 0,5 K… In my opinion, you cannot possibly chose yellowish colours starting at – 0,5 K not knowing that this will affect the overall message in the graphic. What ever the purpose was, this little trick does hide the temperature decline after 1940 to some degree.
And so much more… Data sets from Russia and one named for Chen are shown in comparison, and they show that the Jones and Hansen data are divergent.
I note in passing that even in this graph we have the Arctic as the “over reactor” but in this case with a cold plunge. Guess some “tricks” never lose their punch…
The Russian data set today (2005) – now with a full NH 0-90N coverage – shows almost the full 1940-75 decline it did in 1980. So, while Jones, Hansen and all important players on the “temperature data market” today claims that they have found errors of all kinds, Vinnikov and colleagues, has not found reason to change temperature estimates much back in time:
[graph omitted in my quote -E.M.Smith]
But.. buttom line is: The Vinnikov data is NOT in compliance with Jones and Hansen data after 1984, the corrections for the decline 1938-72 made for Hansen and Jones data is largely still not agreed with by the Russian team. Just a very limitied reduction of the post-1940 decline in the 2005 data – and remember, the 1980 Vinnikov was actually 17,5N-90N while Vinnikov 2005 is full NH.
There is also a nice set of graphs for the Yamamoto dataset, but as the page author notes:
According to Yamamoto, also on global scale the Earth has witnessed quite a decline1958-65, but the data of SH appears slightly too short (?) to say this with confidence.The Yamamoto paper is in Japanese, so I will not give more details for now.
It would seem that we have a niche for a Japanese speaking skeptic to fill, here….
Chock full of wonderful graphs. I can’t reproduce them all here. I’m willing to link to one in the heading, and reproduce the other (as it’s a copy from an earlier published work by a government agency); but too many start to exceed the “Fair Use” guidelines and it’s a fuzzy limit. So again, I’d suggest that you “hit the link”.
There one graph in particular that shows a Land Air Temp Minimum and an Ocean Water Temp Minimum; and shows the lag time between them. The LATM runs from 1964-74 while the OWTM runs from 72-78. An 8 year lag in onset for ocean cooling, then a truncation 4 years after the air temps have started rising. As I remember it, here in California, it snowed in the Central Valley (a VERY rare thing) during those years. I also note in passing that last winter we had snow in Sacramento again…
IMHO, a plot of “showfall in the central valley” would show a reliable and repeatable cold cycle and it would be extraordinarily sensitive to a single degree of warming as the place is right on the edge of ‘no snow ever’. It goes decades without a flake.
These observations seem to support that data are not completely random, but might very well be of useful quality. For example, it does not look like a freak error that SST ends up 0,1 K lower in 1980 than in 1960. In general it appears evident that Land temperatures has a faster variability than SSTand it seems that land vs. ocean temperatures are near equilibrium around 1960-62 and again in 1972-75. That is, even though land temperatures has fast variability (at least in the above examples) SST and land temperatures reaches equilibrium temperature on the longer term. The above illustration is obviously just a scratch in the surface of the science involved. Later we will compare temperatures with Solar activity and ENSO variations.
Further, that 1200 km radius and the use of land data as an ocean proxy is brought into question.
Can we use a 800-1200 km radius from coastal temperature stations, and then claim that huge ocean areas are covered in the land air series?
If you focus on the years 1974-78 it appears that Ocean air temperatures are quite equal to Ocean water temperatures. In this period it seems that the land air series does not very well include this ocean air trend, and episodes like this questions how well ocean air is represented from coastal cities. So maybe the 1200 km radius over ocean from coastal temperature stations is overestimated.
There is also a treatment of the potential for solar involvement (with a very very nice graph):
In the above graphic, I have made some vertical blue and red lines. The illustration shows solar activity (indicated by sunspot number) and then the ENSO index (El nino warming vs La Nina cooling effect).
I made a blue vertical line mostly when solar activity AND ENSO index suggests cooling. I made a red vertical line mostly when solar activity AND ENSO index suggests warming.
Do we see compliance between temperatures and the natural forcings? Blue lines often accompanied by cooling and red lines often accompanied by warming? Yes, to a satisfactory degree.
(In addition, We have not included factors like PDO, AMO, volcanoes etc.)
And there is a pointer to a potentially better data set (that I’ll now be spending a few hours evaluating and potentially testing and / or downloading and… ;-)
It is beyond the scope of this writing to comment on all temperature series, but I find the ERA-40 project impressive. ERA-40 is carried out by the European Centre for Medium-Range Weather Forecasts – ECMWF. In general I recommend all to get acquainted with it, since obviously my comments in the following are just a scratch in the surface and not in any way “the truth”. Check it out for the full story: http://www.ecmwf.int/research/era/do/get/era-40
The ERA-40 project started around year 2000, when an impressive portion of raw data was collected from 15-20 sources, and also the huge pile of SST data from ships. ERA-40 cover temperature data for the years 1958-2001
In 2004, I guess the ERA-40 project was ready with their temperature data series for 1958-2001, but I haven’t seen it widely published. In around 30 writings from ECMWF on te ERA-40 project I have only noticed one person known from the climate gate mails or known from GISS, NOAA, Hadley or CRU. In 2004 it seems that the ERA-40 project has called in Phil Jones to explain something odd. The ERA-40 data did not match the CRU data. In ERA-40, the years 1958-64 appears globally largely as hot as the years 1980-94. (Somewhat like we see in the Raobcore early version). CRU has the 1958-64 around 0,2K colder than ERA-40 compared to modern years. :
That’s a pretty good testimonial for the ERA-40 set to me!
Here the author starts some of his own analysis and makes a decent shot at a more valid temperature trend. Then compares it to some of the others. Again, a load of nice graphs that I’ll not be duplicating here. This is just a “taster” to get you to go read the article. It deserves a close and careful read and a “bit of a think”, even if it is a bit long. A very large body of thought and work is compressed into that one article.
For 1920-today, Hadcrut3v NH shows an approximately 0,33 K warmer trend than the NH estimate of this writing. The extra warming of the Hadcrut temperature appears spread out over all years after 1920. (For the ERA-40 data we saw a 0,32K difference to CRU over the shorter interval 1958-2001)
Again we have HadCRUT warming faster than other, IMHO more accurate, series. I note in passing that recently GIStemp is rising even faster than HadCrut, which makes it a really odd duck…
Even though my starting point with this article was to examine the changes done to temperature data before 1984, it is evident that a significant part of the deviation occurs after 1980, in the years of satellite data.
So I decided to look closer into the years after 1980.
The satellite NH (Land + Sea) data has smaller warming trend than GISS, CRU, Vinnikov and NCDC land and land+SST series. The smoothed CSST curve resembles the temperature data obtained from satellite (UAH + RSS).
BUT: Satellite data represents both Land temperatures and Ocean temperatures – and yet they resemble conventional SST?
Why is the SST trend similar to the satellite land+ocean temperature trend? Satellite temperatures and SST has one thing in common: They are without the warming error from the land/city temperature stations, UHI:
And at this point I’m going to, with only minor shame, link to another of the authors graphs. (I know, I ought to ask for permission, then wait, then write, then… but this is just so important… I’m also fairly sure that, as a link, and for educational purposes, I’m still inside “Fair Use” laws.)
As I’ve asserted before, it looks like it’s the “wrong way UHI” in things like GIStemp and the astounding concentration of thermometers at Airports in recent years in GHCN (reaching over 90% in many locations / countries).
And when the SST matches the satellite/ocean temperature so splendid, this obviously also supports the usefulness of satellite land data – unless satellites temperatures are only reliable over the oceans…!
Bottom line: Satellite data supports the obvious, that land and ocean data will stick together on the long run due to the permanent drift towards temperature equilibrium between land temperature and ocean surface temperatures.
One conclusion I come to from this is that with the ocean temps lagging the land shift, we’re in for a slow ‘catch up’ of the satellite data to the present cold phase on land as the oceans cool. So perhaps part of why HadCRUT and GIStemp are calling this the “Hottest year ever” (don’t they always do that?) is simply because they are still picking up some of that ocean heat that’s still in the ‘getting off the planet’ phase.
To predict our future trend after the cold inflection we’ve just had, the land temps tell you where you are headed, the sea temps where you have been. And the frozen land tells us we’re headed for cold, and for several years as the oceans “catch up”.
The trend difference between CRU land/city temperatures vs. UAH land temperatures amounts to 0,103 K/decade of possibly UHI or siting related faulty warming trend 1980-2007 for land areas. Besides UHI, this extra heat in land/city/airport temperatures might also originate in warming adjustments.
Just for curiosity, what would the “NH ESTIMATE” from this writing look like if we assumed that UHI in general was around just 0,04K/decade? 0,04K/century applied before the UHI free satellite data began in 1980?
Example – If UHI = 0,04K/decade, corrected up to 1980 for the land contribution:
And he then gets a nice graph showing rather close agreement of the sets.
Once again we see that “adjustments”, and UHI are the main things measured by the CRU crew.
The article goes on to lampoon GISS for the way they mis-estimate the percent of the globe that is land vs sea in their results (and an important point in the present GIStemp divergence as the land / sea timing differences bite, IMHO.)
There is then a very nice wrap up and conclusion section that reminds the reader of what has been said and ends with this note:
From here I need to go through SH and thus global data – I aim to have this ready in September 2010.
K.R. Frank Lansner
I’ve not had the time to find out if the SH is done yet, or still a work in progress. But given the care and detail in this work, it would not surprise me if Mr. Lansner took a bit of time to make sure he’d “got it right”.
In any case, I think Frank is well on his way to pointing the rest of us at just were and when the Rewritten Past has had an impact, and with some clues as to the hows and whys.
I suggest reading the article, problably a few times.