I got an email today from Barry Hearn asking me if I knew what was going on with the NCDC data set. It seems that it has started to diverge from GISS, and now is significantly warmer in April 2009.
What is interesting is that while NCDC went up in April, UAH, and GISS both went down. RSS went up slightly, but is still much lower in magnitude, about 1/3 that of NCDC. HadCRUT is not out yet.
Here is a look at the most recent NCDC data plotted against GISS data:
Here is a list of April Global Temperature Anomalies for all four major datasets:
NCDC 0.605 °C
GISS 0.440 °C
RSS 0.202 °C
UAH 0.091 °C
It is quite a spread, a whole 0.514°C difference between the highest (NCDC) and the lowest (UAH), and a 0.165°C difference now between GISS and NCDC. We don’t know where HadCRUT stands yet, but it typically comes in somewhere between GISS and RSS values.
Source data sets here:
NCDC
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.land_and_ocean.90S.90N.df_1901-2000mean.dat
Previous NCDC version to 2007 here: ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.land_and_ocean.90S.90N.df_1961-1990mean.dat
GISS
http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts+dSST.txt
RSS
UAH
http://vortex.nsstc.uah.edu/public/msu/t2lt/tltglhmam_5.2
While it is well known that GISS has been using an outdated base period (1951-1980) for calculating the anomaly, Barry points out that they have been tracking together fairly well, which is not unexpected, since GISS uses data from NCDC’s USHCN and COOP weather station network, along with GHCN data.
NCDC made the decision last year to update to a century long base period, this is what Barry Hearn’s junkscience.com page said about it then:
IMPORTANT NOTE May 16, 2008: It has been brought to our attention that NCDC have switched mean base periods from 1961-90 to 1901-2000. This has no effect on absolute temperature time series with the exception of land based temperatures. The new mean temperature base is unchanged other than land based mean temperatures for December, January and February (the northern hemisphere winter), with each of these months having their historical mean raise 0.1 K.
At this time raising northern winter land based temperatures has not
altered published combined annual means but we anticipate this will
change and the world will get warmer again (at least on paper, which
appears to be about the only place that is true).
So even with this switch a year ago, the data still tracked until recently. Yet all of the sudden in the past couple of months, NCDC and GISS have started to diverge, and now NCDC is the “warm outlier”.
Maybe Barry’s concern in the second paragraph is coming true.
So what could explain this? At the moment I don’t know. I had initially thought perhaps the switch to USHCN2 might have something to do with this, but that now seems unlikely, since the entire data set would be adjusted, not just a couple of months.
The other possibility is a conversion error or failure somewhere. Being a USA government entity, NCDC works in Fahrenheit on input data, while the other data sets work in Centigrade. Converting NCDC’s April value of of 0.605(assuming it may be degrees °F) to Centigrade results in 0.336°C, which seems more reasonable.
Unfortunately, since NCDC makes no notes whatsoever on the data they provide on the FTP site, nor even a readme file about it with anything relevant, it is hard to know what units we are dealing with. They have plenty of different datasets here: ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/
But the readme file is rather weak.
What is clear though is that there has been a divergence in the last couple of months, and NCDC’s data went up when other datasets went down.
So, I’m posting this to give our readers a chance to analyze and help solve this puzzle. In the meantime I have an email into NCDC to inquire.
What REALLY needs to happen is that our global temperature data providers need to get on the same base period so that these data sets presented to the public don’t have such significant differences in anomaly.
Standardized reporting of global temperature anomaly data sets would be good for climate science, IMHO.
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>Standardized reporting of global temperature anomaly data sets would be good for climate science, IMHO.<
Agreed.
Keep up the good work.
Neil,
While I also agree with that thought, I’d like to suggest that at least two —and perhaps more— methods be employed for obvious reasons.
Having everybody reading from the same script might sound nice, but systemic errors can become difficult to detect as a result.
OT so delete if you wish.
ScienceDaily (May 18, 2009) — A team of UC San Diego-led atmospheric chemistry researchers moved closer to what is considered the “holy grail” of climate change science when it made the first-ever direct detection of biological particles within ice clouds.
http://www.sciencedaily.com/releases/2009/05/090517143334.htm
Another article in the “related stories”
“Evidence Of ‘Rain-making’ Bacteria Discovered In Atmosphere And Snow”
http://www.sciencedaily.com/releases/2008/02/080228174801.htm
Made me think, if bacteria can make clouds and UV kills bacteria and UV changes intensity with the solar cycle, could there be a link?
From the article: “bacteria form little groups on the surface of plants. Wind then sweeps the bacteria into the atmosphere, and ice crystals form around them. Water clumps on to the crystals, making them bigger and bigger. The ice crystals turn into rain and fall to the ground. When precipitation occurs, then, the bacteria have the opportunity to make it back down to the ground. If even one bacterium lands on a plant, it can multiply and form groups, thus causing the cycle to repeat itself.”
Yeah… as I was reading this I was thinking, why aren’t these things standardized? I can’t even imagine what my employer’s reaction would be to me releasing poorly documented product. I imagine there are several people working on this stuff, do they not have job descriptions? Or is this being produced for some particular purpose, and releasing it to the public is an afterthought?
Incidentally, and admittedly off topic, the phrase is “all of a sudden”, and it is preferable to use the word “suddenly” instead. Sorry, and no I’m not the language police, but that is one of my very few pet peeves (the other English one being the misuse of “loose” instead of “lose”).
Dumb question – I realise GISS, HadCRUT, NCDC all use surface temps from monitoring stations, whereas UAH and RSS and satelite based.
But what is the difference between GISS, HadCRUT and NCDC ? Do they use data from different monitoring stations ? Do they have differnt methods of making up their data….oops, I mean different methods for analysing their data ? What`s the difference ?
I would have thought there is only the need for one group to monitor the worlds surface stations ?? I`m sure there’s a good reason ?
Perhaps it’s all part of a subtle plan to underline the need for a single US climate and weather service, or as I dubbed it, The Ministry of G!$$ and Wind…
Anthony,
We routinely see the graphs without error ranges. Do GISS, UAH etc report these? Is it possible to show these to provide a more realistic indication of uncertainty, or at least the error range for monthly values. I guess the range between NCDC and UAH does provide some insight on this.
Cheers
MarcH
>Standardized reporting of global temperature anomaly data sets would be good for climate science, IMHO.<
Or increased public access to raw data and methods so errors could be found.
Publishing this data does not take much these days (online is easy and cheap).
And there are decent free tools available (Octave, Python, others).
There is no reason the analysis could not be done completely in the open with help from interested members of the community.
“The other possibility is a conversion error or failure somewhere.”
I am guessing this is probable answer. The possibility that GISS is no longer the warmest temperature anomaly data set seems on previous evidence to be unlikely. Having said that, I am not too concerned about divergence in data sets using surface station data. I believe that Anthony’s work with regard to surface stations shows conclusively that this data source is irrevocably compromised for surface stations rated below CRN-2. I personally pay more attention to satellite data, specifically UAH. UAH has greater coverage than RSS and better satellite altitude maintenance.
Public access to simple tools like Wood for Trees is nice, but you still don’t have access to full data records. You get a few records to compare and trend with some limited tools, but you are still limited.
BTW, check out the new hockey stick at WfT:
http://tinyurl.com/cjguzg
“while NCDC went up in April, RSS, UAH, and GISS all went down”
No they did not, GISS went slightly down (0.47 to 0.44), UAH went sharply down (0.206 to 0.091), but RSS went slightly up (0.194 to 0.202)
REPLY: You are correct, this is what I get for writing after midnight. Fixed, thank you. – Anthony
It is quite a spread, a whole 0.514°C difference between the highest (NCDC) and the lowest (UAH), and a 0.165°C difference now between GISS and NCDC. We don’t know where HadCRUT stands yet, but it typically comes in somewhere between GISS and RSS values.
Anthony (or whoever)
You simply can’t make a direct comparison between the anomalies. They all use different base periods. For example the GISS anomaly relative to the satellite base period (1979-1998) is ~+0.20 deg, i.e. about the same as RSS.
Re: GISS divergence/convergence
GISS seems to have dropped back towards the pack (Hadley, UAH,RSS) since the arctic temperatures started to cool. This makes sense as GISS estimate the arctic by extrapolation.
This doesn’t explain the NCDC anomaly, though.
“It is quite a spread, a whole 0.514°C difference between the highest (NCDC) and the lowest (UAH), and a 0.165°C difference now between GISS and NCDC”
This statement is meaningless. The numbers are not comparable because they are anomalies relative to different base periods.
“While it is well known that GISS has been using an outdated base period (1951-1980) for calculating the anomaly…”
This statement is also meaningless. How can any base period be ‘outdated’? If you want to renormalise to a different one, it’s trivial to do so.
It is not terribly interesting, in any case, to look in detail into a minor difference between two datasets. Look at the graph in mid-2008 and you’ll see a similar example of one going up and one going down. These things happen. It didn’t mean anything then, and it probably doesn’t mean anything now.
The NCDC is detecting a leading hot air mass from the Copenhagen Alarmfest. The other temperature series are not as politically sensitive.
Some years ago, GISS started to diverge from the other 4 data sets, and become warmer. There were two possible explanations for this; GISS was cooking the books, or by extrapolating to the poles, GISS was measuring a significant difference. I always hoped the latter was correct, and GISS were doing proper science. Now the data indicates that the poles are cooling. So what is being observed is a return of the GISS data to where the other data sets always have been. The key issue to me is, however, quite different. RealClimate and the warmaholics have nailed their colors to the mast in using GISS data to support the idea that global temperatures are still rising. The GISS data was the last of the 5 to show that global temperature anomalies were falling. Now it is going to be much more difficult for the warmaholics to explain that temperature anomalies are really rising, when they have been falling for several years.
Anthony: As you’re aware, GISS uses NCDC’s OI.v2 (Optimum Interpolation) SST anomaly data from December 1981 to present, while the NCDC uses its ERSST (Extended Reconstructed) data. But there was a recent change in one. For its global surface temperature anomaly product, the NCDC recently switched versions of SST anomaly data from ERSST.v2 to ERSST.v3b.
There are differences between OI.v2 (used by GISS) and ERSST.v3b (used by NCDC). Here’s a comparative graph of the two global SST anomaly datasets from November 1981 to present.
http://i41.tinypic.com/vdz3h3.jpg
And here’s a graph of the difference (ERSST.v3b MINUS OI.v2 SST).
http://i44.tinypic.com/jt5ldc.jpg
Some of the difference should be due to the use of satellite data. OI.v2 uses satellite, buoy and ship sampling. ERSST.v3 (no “b” in the suffix) originally used the satellite data, primarily to supplement buoy and ship data where they’re sparse in the high latitudes of the Southern Hemisphere (in other words, the Southern Ocean). Users must have complained about the early timing of the drop in the Southern Ocean data, because the NCDC deleted the satellite data in the recently released ERSST.v3b data.
I wrote a quick post on the ERSST.v3 versus ERSST.v3b data a couple of months ago, for those who are interested:
http://bobtisdale.blogspot.com/2008/12/unheralded-changes-in-ersstv3-data.html
And two more posts that were a closer looks at the ERSSST.v3b data:
http://bobtisdale.blogspot.com/2009/03/knmi-added-ersstv3b-data-to-climate.html
http://bobtisdale.blogspot.com/2009/04/closer-look-at-ersstv3b-southern-ocean.html
I’m trying to finish a post that I’ve been working on for over a week (Why Did the Ocean Heat Content of the Atlantic Rise So Fast? Its Rise More Than Doubled Those of the Indian and Pacific Oceans). It’s a follow-up to my look at the Levitus et al (2009) OHC data on a per ocean basis.
http://bobtisdale.blogspot.com/2009/05/levitus-et-al-2009-ocean-heat-content.html
But when I’m done with that post, I’ll work on one that examines the differences between the OI.v2 and ERSST.v3b SST anomaly datasets. I’ll email you when I’m done with it.
Regards
REPLY: Thanks Bob, I’ll look forward to your analysis and what it may reveal. – Anthony
Stupid non-scientist question!!
In my young days I had a boss who taught us all that the business bottom line was all about cash. Percentages were a guide but what mattered to him at the end of the day was having the money. “I can’t buy food with percentages,” he used to say.
And I can’t plan next week’s trips to the coast or wherever on “anomalies”. I need to know what the real temperature is or is going to be but all I get is a lot of very clever people choosing a set of figures that suits them and then trying to tell me that this month is a small fraction of a degree more or less than the small fraction of a degree more than it was last month or last year.
It seems we don’t know what the earth’s actual temperature is or we have no way of measuring what it is (which is something that even Hansen admits) or even what it ought to be and we have five different organisations telling us five different things based on five different sets of figures and none of those tell us anything of practical use about the state of the climate or the weather.
Where am I going wrong?
I only ask because it would be nice to know.
Good thing these “adjustments” only apply to the paperwork and not to the real world.
I prefer having differences between the datasets. If you understand the differences and the reasons for them, you can determine why one is used for a particular study and not the others.
Example, global ERSST (NCDC) data (all versions) has a dip and rebound from the 1880s to 1940s, where global HADSST data does not. HADSST has a more continuous rise. In other words, there’s no significant difference in the global ERSST data values in 1880 and in 1976. Global ERSST anomalies dropped and came back up–no big deal. So when climate modellers or the IPCC try to reproduce the global temperature record, they use Hadley Centre data because it doesn’t include that inconvenient dip and rebound and is therefore easier to “duplicate” with contrived forcings.
Also, to standardize the GISS, Hadley Centre and NCDC products, you’d have to get them to agree on infilling, smoothing, etc. Fat chance of that.
I have a version from a few months ago and there is almost no change between the older and newer series until the last decade or so.
Then the changes seem to grow a little on an increasing trendline (0.003C per decade) versus the older series. The changes are still small with the biggest positive change being +0.062 in Jan 2006 and the biggest reduction being -0.015C in Nov 2008.
As these series are updated over time with new temps and the discovery of errors, this kind of change would be expected, although these changes are a little higher than they should be and there shouldn’t be an increasing trendline. (Theoritically of course, but this is climate science and the majority of adjustments made to the temperature record have been positive to date).
But it does look something might be becoming unstable as the swings are rising in amplitude beyond what should be occurring.
Anthony,
Off topic. I would like you to offer you a guest post. How would I go about this?
Reid,
It’s either that or they are using measurements from instruments located in Washington DC. All that hot air is bound to cause anomalies and an increase in NCDC readings.
Sven (02:41:37) :
Confirmed. The article needs adjusting.
Highlander,
I have to agree with you. Better to allow different measurements of temperature be presented, using different methods and systems to derive their results. That way it does become much easier to spot and analyse systemic problems.
It also encourages a healthy debate and much needed scepticism.
So in this case there is every probability that NCDC have made a mistake somewhere.
There remains though, a small possibility, that everyone else has it wrong.
Best to go back to the raw data and check.
The difference between 1880 and 2009 is 0.050 to 0.150=0.100, a tenth of a degree!!. That is a NANO GLOBAL WARMING!!!!