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While it is well known that GISS has been using an outdated base period (1951-1980) for calculating the anomaly, Barry points out that they have been tracking together fairly well, which is not unexpected, since GISS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.
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
Anthony
I endorse John Peter’s recommendation on numbering.
I have not used any, but there may be some WordPress numbering plugins or methods to do it. e.g.
K.S. suggests it is possible: “Yes you can definitely do this. The easiest way to do it would be to look into themes that have numbered comments, or a plugin that does the same. Otherwise you could manually adjust your comments.php page.”
Greg’s Threaded Comment Numbering: Number Your WordPress 2.7 Comments the Easy Way claims to add numbering.
WordPress @ur momisugly T2 gives code examples of the steps involved.
ClimateAudit provides comment numbers, and I thought it was using WordPress.
Maybe some reader has the expertise/experience to help.
REPLY: I’ve dealt with this issue before, the answer is simply “no”. I can’t choose a theme like CA uses, I can’t easily make my own customizations. wordpress.com does not offer these things unless I move WUWT to either a VIP server $600 per month, or separate external server, which I don’t have the time nor inclination to manage.
The same goes for the other most popular request, comment preview, though I’ve asked for it from WP.com. I use this free service gratefully, but it has limitations that I have no control over. – Anthony
GISS Surface Temperature Analysis
Updated Jan. 13, 2009, with calendar year data.
Given our expectation of the next El Niño beginning in 2009 or 2010, it still seems likely that a new global temperature record will be set within the next 1-2 years, despite the moderate negative effect of the reduced solar irradiance.
This has probably been covered by an article on WUWT but I probably missed it. It will be interesting if it unfolds thus.
http://data.giss.nasa.gov/gistemp/2008/
I smell a rat or rats! I simply don’t trust any govermental agency anymore, for good reason I think!
“GISS is behind the times…”
This is simply not meaningful. The choice of reference period is completely irrelevant to any analysis. You can trivially renormalise to whatever period you choose. If their reference period was 1880-1910, or if it was 1979-2009, it would make absolutely no difference to anything.
“The base period they chose starting in 1951 is a cooler period globally”
Not really. Cooler than today, that’s for sure. It’s a thing called ‘global warming’. Not cooler than times before it. In fact, the mean anomaly during the base period (zero, by definition) and during the 20th century (-0.02°C) are almost equal.
“to change it to reflect proper base period reporting would cause the slope of the GISTEMP graph to drop, and look “less alarming”.”
There is no ‘proper’ base period, and changing it would make no difference at all to the slope of the graph. It would make no difference to anything.
“”” Sam the Skeptic (04:36:33) :
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. “””
Well more importantly Sam; even if we could measure the real surface or lower troposphere mean global temperature; it would tell us exactly nothing about climate. It won’t even tell us whether the earth is heating up or cooling down; because energy transport is not simply related to temperature. Some thermal processes are linear with temperature differences; while others may follow fourth power or fifth power of temperature. There are no temperature differences in an average anomaly number. Then the actual energy processes are very dependent on location and terrain; not to mention the local biology.
So as RW said above; it is not very interesting to talk about minor small differences in different data sets; and even less so to report in millidegrees of some unspecified scale when global surface temperature can cover 150 deg C total range at some instant of time.
I heard a report on this morning’s news about artificial turf being used as an Astroturf substitute; made out of old tire rubber, and the report claims that the surface temperature on that stuff reaches 140 deg F; which is +60 deg C. So I would expect real ground surfaces to exceed that in the hottest places.
Have you read the Monckton´s report? It says something about NCDC..
http://scienceandpublicpolicy.org/images/stories/papers/reprint/markey_and_barton_letter.pdf
Mann Hockey stick: disgusting
GISTEMP record manipulated back in time: outrageous
NCDC boss Tom Karl lying at Senate Committee hearing: priceless
Anthony,
A simple check says there is nothing here. It’s trivial to rebaseline the series to the same period, but you dont even have to do that. An anomaly series is merely the raw series shifted up or down by a constant. and what you are looking for is some trend in the difference of the anomaly series.
From 1880 to 2009 The differences between GISS and NCDC looks like this
MAXIMUM =0.2298
MINIMUM = -0.3437
AVERAGE = -0.030139369
STANDARD DEV = 0.073151392
SLOPE of GISS- NCDC = 3.82089E-05
Hmmm! I may have to retract my earlier comment. I’m having trouble identifying the SST anomaly data used by NCDC in the global temperature product. Their Global Surface Temperature Anomalies webpage says it’s SR05 data:
http://www.ncdc.noaa.gov/oa/climate/research/anomalies/index.php
But the SR05 webpage says it’s experimental and there’s no data available through the links:
http://www.ncdc.noaa.gov/oa/climate/research/anomalies/anomalies-experimental.html#anomalies
Somewhere along the line I read or was given the impression that they were now using ERSST.v3b data, and that they had discontinued updating their ERSST.v2 data, though I can’t find any reference to either. I’ll keep looking.
One difference with GISS is that they don’t actually use any polar data measurements. The temperature reported in the polar regions is extrapolated from Hansen’s own models according to the last information I have. One source of a difference could be actual readings vs. calculated fill data.
GISS is out of step with the real world: click
Everyone else shows declining temperatures. When GISS “adjusts” their raw data, they show non-existent warming. Not surprising, with Hansen at the controls.
Another possibly interesting source of difference could be the GISS adjustment mechanism. GISS uses averages to fill in missing values from the past. When temperatures are warming, it means that with each monthly data set, the past is also adjusted warmer when calculating fill values from average. The current warmer sample increases the “average” and so that value is plugged into the past.
When temperatures are cooling, the reverse is true. The average declines and so calculated fill values representing past temperatures decline. So if this month cools, any missing values for last month that were calculated from averages also cool a little making the divergence greater this month than it was last month. The GISS adjustment mechanism is a positive feedback of sorts that causes changes today to “change” the past. In a period of cooling temperatures, we should see a cooling of all past temperatures where missing values are calculated from a declining average and incorporated into the gridded averages.
realitycheck (09:05:05) :
Re: Frank Lansner (08:05:08) :
“Check out the picture where I compare the pacific.
In NOAA´s version the PDO is almost neutral, but in the Unisys version the PDO is very very strong. You have a cold pacifis by Unisys and a warm pacific by NOAA.”
Nathan Mantua’s page here shows the official monthly CDC value for the PDO index…
http://jisao.washington.edu/pdo/PDO.latest It has kept the PDO strongly negative through April.
I’m glad someone has brought this up — that the canonical measure of the PDO is still strongly negative, and the latest — April — even went more negative just a bit.
I, too, have been pondering the difference between the Unisys page and NOAA’s image. Again, as in GISS vs. NCDC, or whatever, we have to ask what the base period is. I’m going to look into this further, as far as NOAA vs. Unisys is concerned. I suspect that Unisys is using a standard WMO climatological baseline of 1971 to 2000. But NOAA? We’ll see.
And…. If you rebaseline GISS to the same time period as NCDC you get
the following for GISS-NCDC
MAXIMUM= 0.2492417
MINIMUM = -0.3242583
AVERAGE = -0.010697669
STDEV= 0.073151392
SLOPE of GISS-NCDC= 3.82089E-05
For April 2009 on a rebaselined basis Giss-NCDC = -0.1455583.
Ya, NCDC is warmer. its a 2 sigma event. nothing to write home
about. and the trend of GISS-NCDC, is still zero. now this is just a simple test, so one might want to investigate if there is some pattern to the differences or time dependencies.. and its kinda interesting that the negative tail is longer..
And my comment immediately preceding can sort of be checked to see if last month’s divergence from NOAA is greater this month that it was last month.
In other words, did the amount of the previous month’s divergence increase this month?
George E. Smith (09:22:41)
Thanks for that reply. I just about understand the science of that (thanks to this site, mainly) but it only makes things more puzzling for the layman.
I know that an anomaly of +.02 compared with last year’s +.025 means that things are cooler but only if the period of comparison is the same and if the period of comparison is changing then surely the figures become meaningless.
You can pick what figures you like to prove what you like and that goes for the skeptics as much as for the alarmists.
I also understand that temperature is not the be-all and end-all of the argument but until the man-in-the-street understands, for example, that heat and temperature aren’t the same thing we’re going to keep on getting suckered by the warm-mongers and their doomsaying.
I noticed some time ago that the NCDC monthly data for land and ocean has adjustments that often go back many years. I matched up their latest offering with my plotting data and the earliest change goes back to 12/1999.
It’s by a trivial amount -0.0001, but I’m mystified as to why they do it. This may be true of their other data sets but I haven’t had time to check.
I thought that was “Something Wicki This Way Comes”.
[snip OT]
Here are monthly temperatures … not anomalies:
http://junkscience.com/GMT/NCDC_absolute.gif
I think I stole this from Smokey…
Anthony,
This divergence is not particularly noteworthy (and not beyond 2 standard deviations in the variance between the two data series). There are months where they diverge just as much (or more) in 2007, 2005, 2004, 2003, 2002, 2001, 2000, etc. Your initial graph is slightly misleading because you do not put both series on both baselines.
Here is 2000 to present standardized on a 1979-2008 baseline:
http://i81.photobucket.com/albums/j237/hausfath/Picture55.png
First: This has been a good post with good comments. Thanks to all of you with info and insight.
Second: It took me just a few reads here on WUWT to feel comfortable with the limitations some are complaining about. I now even enjoy it when someone corrects the grammar and spelling (even their own) and sometimes I even learn something new. And on some other slightly more complicated sites I still don’t know what is happening when I hit the submit button. Simple is better – and cheaper. Everyone just relax.
Third: OT – Mitch Daniels, Republican governor of Indiana had a great opinion piece in Friday’s WSJ (May 15) which they put under the title “Indiana Says ‘No Thanks’ to Cap and Trade.”
An interesting note on the importance of using a common baseline.
Here is my version of Anthony’s graph in the original post. In it, the current divergence seems unusual, at least since 2007:
http://i81.photobucket.com/albums/j237/hausfath/Picture56.png
Here is a correction of Anthony’s graph that puts both data series on the same baseline (1979-2008 in this case). Now we see that the current divergence is smaller than a divergence that occurred in 2007:
http://i81.photobucket.com/albums/j237/hausfath/Picture57.png
REPLY: Thanks for doing that. The real question is, which of these is the correct global temperature anomaly for April ?:
NCDC 0.605 °C
GISS 0.440 °C
RSS 0.202 °C
UAH 0.091 °C
HadCRUT ?? (not yet published)
The general public has not the skill to discern the nuances of baselines and methods. – Anthony
Frank Lansner (08:05:08) :
Want to see something “Hinky”?
Differences between NOAA and Unisys appears to reach new hights!
http://www.klimadebat.dk/forum/klimadebatens-fordrejninger-og-forfalskninger-d12-e556-s200.php#post_12170
Check out the picture where I compare the pacific.
In NOAA´s version the PDO is almost neutral, but in the Unisys version the PDO is very very strong. You have a cold pacifis by Unisys and a warm pacific by NOAA.
Frank,
If I’m reading the provenance of the NOAA pic correctly, it is this:
The original 36 km satellite-only reprocessed SST data used for creating the climatologies were generated from the Multi-Channel SSTs (MCSSTs) by the Rosenstiel School of Marine and Atmospheric Science (RSMAS) of the University of Miami (Gleeson and Strong, 1995). In-situ SSTs from drifting and moored buoys were used to remove any biases, and statistics were compiled with time to derive the reprocessed SSTs. The monthly mean SST climatologies were then derived by averaging these satellite SSTs during the time period of 1985-1993, with observations from the years 1991 and 1992 omitted due to the aerosol contamination from the eruption of Mt. Pinatubo. These climatologies were developed at NOAA/NESDIS/STAR (then ORA) before being delivered to NESDIS/OSDPD for implementation. The 36 km climatologies were finally interpolated into 0.5-degree (50-km) resolution to match the resolution of the operational SST analysis field. These operational monthly mean climatologies are used for producing our operational SST anomaly products.
Source: http://coralreefwatch.noaa.gov/satellite/methodology/methodology.html#clim
I added the bold for emphasis.
The Unisys product, on the other hand, uses a standard 1971-2000 climatology. Whereas the NOAA product is using 1985-1993, with two cool years removed, as its “normal” in the NOAA graphs.
I believe there is some confusion regarding “measurement error” and “error bands.” The temperatures being discussed would have measurement error for all the reasons explained in the “surface stations” reporting Anthony has conducted and reported on. An extension of a “best fit” line to a data set (a projection of future temperatures, perhaps) could have error bands. I don’t believe these are the same. [Someone with better expertise than I have might offer a proper exposition of this issue.]
[snip OT]