OR…. There are Increases in Trend with Each Update While The Causes of Downward Biases Are Deleted
Guest Essay by Bob Tisdale:
In the recent WUWT post Something hinky this way comes: NCDC data starts diverging from GISS, the differences between GISS and NCDC global temperature anomaly data was discussed. I commented that the GISS and NCDC global surface temperature anomaly data relied on two different SST datasets.
NCDC has their own SST anomaly dataset for their global surface temperature product, and they calculate anomalies against the base years of 1901 to 2000. GISS has used the NCDC OI.v2 SST anomaly data since December 1981, and before that they had used the Hadley Centre’s HADSST data. GISS then splices the two datasets together. This post does not discuss the HADSST data, but delves into the differences between the multiple NCDC SST anomaly datasets, one of which is used by GISS.
GRAPHS OF GLOBAL OI.v2 (USED BY GISS) and “NCDC Ocean” SST ANOMALY DATA
I have not been able to find GISS SST anomaly data as a separate dataset, so for a short-term comparison, I’ll use their source, the OI.v2 SST anomaly data available through the NOAA NOMADS system. Unfortunately, the OI.v2 SST data uses a third climatology for their anomalies (with base years of 1971-2000), but don’t let that concern you. It just makes for an unusual comparative graph.
Figure 1 is a short-term comparison (November 1981 to April 2009) of the OI.v2 Global SST anomaly data (used by GISS) and the NCDC’s “Global Ocean Temperature”. The NCDC data is available toward the bottom of the NCDC Global Surface Temperature Anomalies webpage here:
http://www.ncdc.noaa.gov/oa/climate/research/anomalies/index.php
Specifically:
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.ocean.90S.90N.df_1901-2000mean.dat
http://i41.tinypic.com/sec4kh.jpg
Figure 1
The two datasets appear to track one another, and the obvious difference, the shift in the data, is a result of the different base years. But if we subtract the OI.v2 SST data from the NCDC “Global Ocean” SST anomaly data, we can see that one dataset rose more than the other since November 1981. Refer to Figure 2. The NCDC “Global Ocean” SST anomaly dataset rose at a greater rate than the OI.v2 SST anomaly data that’s used by GISS. This would bias the NCDC global surface temperature upward over this time span, or bias the GISS data down, depending on your point of view.
http://i39.tinypic.com/qzlsvo.jpg
Figure 2
So to conclude this section of this post, part of the difference between the GISS and NCDC global surface temperatures discussed in WUWT post Something hinky this way comes: NCDC data starts diverging from GISS results from the use of different SST anomaly datasets.
WHAT’S THE DIFFERENCE BETWEEN THE TWO DATASETS?
The use of satellite data appears to have an impact.
NOAA describes the Optimum Interpolation (OI.v2) SST anomaly data (used by GISS) as, “The optimum interpolation (OI) sea surface temperature (SST) analysis is produced weekly on a one-degree grid. The analysis uses in situ and satellite SST’s plus SST’s simulated by sea-ice cover.” The in situ data is from buoy and ship measurements. The full description of the OI.v2 data is here:
http://www.cdc.noaa.gov/data/gridded/data.noaa.oisst.v2.html
The NCDC identifies the “Global Ocean Temperature” dataset as SR05 in its Global Surface Temperature Anomalies webpage:
http://www.ncdc.noaa.gov/oa/climate/research/anomalies/index.php#sr05
Linked to the webpage is a paper by Smith et al (2005) “New surface temperature analyses for climate monitoring” GEOPHYSICAL RESEARCH LETTERS, VOL. 32, L14712, doi:10.1029/2005GL023402, 2005.
http://www.ncdc.noaa.gov/oa/climate/research/Smith-comparison.pdf
On page 2, Smith et al describe the SR05 data as, “The SR05 SST is based on the International Comprehensive Ocean Atmosphere Data Set (ICOADS [Woodruff et al., 1998]). It uses different, though similar, historical bias adjustments to account for the change from bucket measurements to engine intake SSTs [Smith and Reynolds, 2002]. In addition, SR05 is based on in situ data.”
It appears, from that quote and the rest of the paper, the SR05 SST dataset does NOT use satellite data. This is consistent with NCDC’s other long-term SST datasets. They also abstain from satellite data.
COMPARISON OF SR05 TO THE NCDC’s OTHER TWO SST ANOMALY DATSETS
In addition to the SR05 SST data, the NCDC also has two other long-term SST datasets called Extended Reconstructed SST (ERSST) data. The ERSST.v2 (Version 2) data was introduced in 2004 with the Smith and Reynolds (2004) paper Improved Extended Reconstruction of SST (1854-1997), Journal of Climate, 17, 2466-2477. Many of my early Smith and Reynolds SST Posts used ERSST.v2 data through the NOAA NOMADS system. Unfortunately, ERSST.v2 data is no longer available through that NOAA system, so the latest ERSST.v2 global SST anomaly data from NOMADS I have on file runs through October 2008.
The ERSST.v2 data was updated with ERSST.v3 data. In my opinion, it provides the most detailed analysis of high latitude SST in the Southern Hemisphere (the Southern Ocean). The ERSST.v3 data was introduced last year with the Smith et al (2008) paper: Improvements to NOAA’s Historical Merged Land-Ocean Surface Temperature Analysis (1880-2006), Journal of Climate,21, 2283-2296. The NCDC updated it with their ERSST.v3b version later in 2008, but more on that later. A limited number of datasets (based on latitude) for the ERSST.v3b data are available from NCDC (though it is available on a user-selected coordinate basis through the KNMI Climate Explorer website, as is ERSST.v2 data).
I have found no source of SR05 SST anomaly data, other than the Global, Northern Hemisphere, and Southern Hemisphere “Ocean Temperature” datasets linked to the Global Surface Temperature webpage.
Figures 3 and 4 are long-term comparisons (1880 to “present”) of the “NCDC Global Ocean” (SR05) SST anomaly data to the ERSST.v2 and to the ERSST.v3b SST anomalies. Based on the linear trends, the “NCDC Global Ocean” (SR05) data resides between the older ERSST.v2 and the more recent ERSST.v3b data.
http://i40.tinypic.com/am84ma.jpg
Figure 3
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http://i43.tinypic.com/2u9pwk6.jpg
Figure 4
But note that the trend increases with each SST dataset improvement.
THE ERSST.v3 DATASET ONCE USED SATELLITE DATA
In “Improvements to NOAA’s Historical Merged Land-Ocean Surface Temperature Analysis (1880-2006)”, Smith et al note the use of satellite data for ERSST.v3 data in their abstract, “Beginning in 1985, improvements are due to the inclusion of bias-adjusted satellite data.” That’s a positive description. They further proclaim, “Of the improvements, the two that have the greatest influence on global averages are better tuning of the reconstruction method and inclusion of bias adjusted satellite data since 1985.” In fact there is a whole subsection in the paper about the satellite adjustments.
WHY THEN DID THE NCDC DELETE THE SATELLITE DATA IN THE MOST RECENT VERSION, ERSST.v3b?
Reynolds, Smith, and Liu write in a November 14, 2008 attachment to their main ERSST.v3b webpage, “In the ERSST version 3 on this web page WE HAVE REMOVED SATELLITE DATA from ERSST and the merged product. The addition of satellite data caused problems for many of our users. Although, the satellite data were corrected with respect to the in situ data as described in reprint, there was a residual cold bias that remained as shown in Figure 4 there. The bias was strongest in the middle and high latitude Southern Hemisphere where in situ data are sparse. THE RESIDAL BIAS LED TO A MODEST DECREASE IN THE GLOBAL WARMING TREND AND MODIFIED GLOBAL ANNUAL TEMPERATURE RANKINGS.” [Emphasis added.]
The link for that quote is here:
http://www.ncdc.noaa.gov/oa/climate/research/sst/papers/merged-product-v3.pdf
Note that the “merged product” referenced above is their ERSST.v3b-based land plus sea surface temperature data.
Figure 5 illustrates the difference between the ERSST.v3b and ERSST.v3 global SST anomaly data (ERSST.v3 data MINUS ERSST.v3b data). The “dip” after 1985 would appear to be the satellite bias.
http://i43.tinypic.com/6yfx8h.jpg
Figure 5
Hmmm. It looks as though, if you’re a SST data producer, downward biases are bad, but increases in trend with each update are good.
SOURCES
The ERSST.v3b SST anomaly data is available through the NCDC’s ERSST.v3 webpage:
http://www.ncdc.noaa.gov/oa/climate/research/sst/ersstv3.php
Link to the available datasets:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo
I used this dataset for this post:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo/aravg.mon.ocean.90S.90N.asc
The NCDC’s “Global Ocean Temperature” dataset is available through:
http://www.ncdc.noaa.gov/oa/climate/research/anomalies/index.php
Specifically:
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.ocean.90S.90N.df_1901-2000mean.dat
ERSST.v2 data are no longer available through the NOAA NOMADS System. I relied on ERSST.v2 global SST anomaly data from my files for this post. I also used the ERSST.v3 I also had on file for the comparison to the ERSST.v3b data.
The OI.v2 data is available through the NOAA NOMADS system:
http://nomad3.ncep.noaa.gov/cgi-bin/pdisp_sst.sh?lite
Huh guys, this trend is really residual. It’s about 0.25 C per century, that is 0.025C per decade.
In fact looking at the curve it’s obvious the differences hinted at in a previous post are within the “noise” typical of the two data sets, the contribution from the trend bias isn’t important. There is no hint of fraud. And I suggest people don’t use the expression when the changes in the product are documented and alluded to by the authors.
And after seeing the larger plot contributed by Lubos, for me the issue is settled. My feeling is that if you plot an histogram of the difference between data sets, the April anomaly would fall within the non-outlier range.
Perry Debell (08:11:49) :
From the BBC “news” story:
Wayne Elliott, Head of Health Forecasting at the Met Office, said: “Summer is nearly with us and it’s a good time to prepare for the high temperatures that we can experience in this country.”
—
I wonder how folks in Britain were ever able to prepare for summer in the past without the sage wisdom from the MET office to guide them…
Imagine that – a summer with warm temperatures!! Next thing you know, they’re going to predict a winter with cold temperatures…
This may seem out of topic, but in a sense it is relevant to the whole scene.
http://news.bbc.co.uk/2/hi/technology/8052798.stm
A web tool hailed as a significant rival to search giant Google has gone live to the public.
Wolfram Alpha is called a computation knowledge engine rather than a search engine and wants to change the way people use online data.
…….
During a demonstration at Harvard University’s Berkman Center for Internet and Society, Dr Wolfram said: “Our goal is to make expert knowledge accessible to anyone, anywhere, anytime.”
We should think of crucial questions to ask about “global warming NOT”. There is great danger of this becoming a great tool for the climate “consensus”.
They are at it again.
Gubment Cheddar funds study at MIT that concludes:
Climate Odds Much Worse Than Thought.
http://www.sciencedaily.com/releases/2009/05/090519134843.htm
This is getting out of hand. WWUT is gonna have a big, I Told You So and soon!
The Boy of John
John Boy (12:23:30) :
Here, buried near the end of the article, is all you need to know about this junk science:
Prinn stresses that the computer models are built to match the known conditions, processes and past history of the relevant human and natural systems, and the researchers are therefore dependent on the accuracy of this current knowledge. Beyond this, “we do the research, and let the results fall where they may,” he says. Since there are so many uncertainties, especially with regard to what human beings will choose to do and how large the climate response will be, “we don’t pretend we can do it accurately. Instead, we do these 400 runs and look at the spread of the odds.”
—
The money quote from above:
“…we don’t pretend we can do it accurately.”
I propose that we make this NOAA’s new motto.
“Why do the “corrections” always seem to go one way?”
Because they are only human: If things go the way they expect, then they don’t bother scrutinising the data/method. But if it goes contrary to what the expect, then they look for errors, and of course *sometimes* find them (no malice required). The upshot of this is that there are a LOT of errors going in the *other* direction that have not been spotted!
“Why do the “corrections” always seem to go one way?”
Because they are only human: If things go the way they expect, then they don’t bother scrutinising the data/method. But if it goes contrary to what the expect, then they look for errors, and of course *sometimes* find them (no malice required).
The upshot of this is that there are a LOT of errors going in the *other* direction that have not been spotted!
“This is getting out of hand. WWUT is gonna have a big, I Told You So and soon!”
There is never going to be an I told you so…..Obama is on the move and your life will change forever. I was wondering why the auto compaines were in of today’s announcment…there is the answer
Today’s bitter deal was sweetened with further funds: $15bn in loan guarantees in the economic recovery plan and the prospect of a further $50bn in allowances under the climate change bill now making its way through Congress.
We are going to pay for it all……once oil usage drops, higher taxes will be needed to replace less fuel sold.
Bob Tisdale,
Is there any way to subtract out the biases add in, so we can get an honest answer?
It would seam as thought here in Michigan we have been cooling all along, less the occasional warm ups.
TX
They are pretty slippery there at MIT, Frank!
Thanks,
The Boy of John
The money quote from above:
“…we don’t pretend we can do it accurately.”
I propose that we make this NOAA’s new motto.
I agree.
George E. Smith (10:22:15) :
. . . In particular it always cools down at night when there are clouds in the sky; it never warms up after the sun goes down; cloud or no cloud (assuming some new warm air mass doesn’t move in from some other place).
Nighttime clouds act as a blanket. You get the coldest temps on cloudless nights due to radiative cooling.
You’re right that the overall cloud effect is negative, and that “sensitivity” is a phony baloney factor invented to cover the fact that CO2 by itself can’t contribute enough warming to notice.
Bob Tisdale
Hmmm. It looks as though, if you’re a SST data producer, downward biases are bad, but increases in trend with each update are good.
AGWers created a warming world at their wish. During the last 19 years they have been trying to discredit and/or erase the knowledge on paleogeology, paleoclimatology and paleobiology which had been done with the strict appliance of the scientific method by many, many honest and dedicated researchers. As from AGW hysteria, everything which proves the falseness of their idea on a warming world is denied systematically. Since the raising of AGW, satellites sensors are biased, proxies are invalid, chemical methods to obtain the concentration of CO2 in the atmosphere is obsolete, the Holocene Optimum never happened, the Medieval Warming Period never occurred or it was not global, the emissivity of CO2 is compared with that of a blackbody, the atmosphere is a blackbody, etc. Previous arguments are strongly backed by unscientific sources, like Media. Their protection for not being exposed is to blame realist scientists of being “deniers”, when the latter term perfectly fits to AGWers.
BTW, saying that the fluctuations of the solar energy have nothing to do with Earth’s climate is misguided… Isn’t the Sun the main source of energy for the whole solar system? Isn’t the climate a subject on energy instability (entropy flux) when it is dispersed or diffused from one system to other systems?
http://biocab.org/Amplitude_Solar_Irradiance.html
If you have the kindness on reading the article, please consider that the correlation coefficients correspond to year to year calculations. Thank you! 🙂
Did you notice how MIT tried to legitimize thier ‘research’?
400 runs of the model with each run using slight variations in input parameters (see below for a good laugh),
selected so that each run has about an equal probability of being correct based on present observations and knowledge… (scoff!)
the MIT model is the only one that interactively includes detailed treatment of possible changes in human activities as well – such as the degree of economic growth, with its associated energy use, in different countries
AND here’s the real kicker!!
they supposedly based their runs on ‘peer reviewed literature’ for economic activity, atmospheric, oceanic and biological systems.
So they supposedly used peer reviewed values for economic, oceanic, and atmospheric variables and looked at 400 different scenarios. And they used our tax dollars to do it!
What a waste!
The Boy of John
For some reason my previous post was “eaten” by the system… Please, tell me what could have happened. I submitted it and it disappeared immediately I clicked on the submitting comment button.
Reply: For some reason it ended up in the spam filter. It’s been rescued and posted. ~dbstealey, moderator
Thanks a lot, dbstealey moderator… I think what the reason was; I’m sorry. 🙂
I realize that this is off topic, but has anybody noticed cryosphere today is showing changed data in the sea ice area for several regions? For example, they are showing the Barents Sea dropping about 200,000 km2 in the last few days. That was not the case yesterday.
Tom
ClimateSanity
“”” Mike McMillan (13:38:02) :
George E. Smith (10:22:15) :
. . . In particular it always cools down at night when there are clouds in the sky; it never warms up after the sun goes down; cloud or no cloud (assuming some new warm air mass doesn’t move in from some other place).
Nighttime clouds act as a blanket. You get the coldest temps on cloudless nights due to radiative cooling. “””
Mike you also get cold temperatures on cloudy nights due to radiative cooling; you just don’t get as much cooling. You get the coldest nights where it is also dryest since you don’t get water vapor warming either; and just look at how ineffective CO2 is at warming the surface on a cold dry night when there is no water vapor around. So much for CO2 greenhouse warming !
My objection to this cloudy night thing being traipsed out by the warming crowd; is that they offer this night time “blanket”, which I don’t disagree with, as a positve feedback cloud warming effect. Baloney, or BALONEY; that was last night’s weather not climate; and the isssue is if you have an increase in cloud cover over climatically significant time frames (why not 30 years) IT COOLS DOWN ! It NEVER warms up, when total global cloud cover increases; because those cloud increases that do slow down the night time cooling, (it still cools) block a whole lot of sunlight, and reflect more, during the daylight hours; which cools the surface.
And it is surface temperatures which determine any feedback effects.
You need hotter surface temperatures to get more water vapor evaporation; and you need hotter surface temperatures to get more oceanic CO2 outgassing. Hotter atmospheric temperatures may eventually warm the ground a little but they also enhance the radiation to space, which is ultimately the only significant global cooling mechanism.
I read a paper by some British University “rocket scientists” who modelled cloud behavior on their playstation in the presence of a CO2 doubling. In their computer model run, that caused clouds to evaporate so they put that down as a positive feedback cloud effect; ergo clouds are positive feedback.
Did I mention that during this computer video game run; they clamped the surface temperature AT A FIXED VALUE !!!
Who licensed them to make up their own Physics laws like that ? If they had left well enough alone; and not clamped the surface temperature; they would have discovered the obvious, that you can discover with a stick on a sandy beach on a desert island. If you double the CO2, and don’t clamp the surface temperature; it will increase slightly, which will evaporate more water vapor; which will increase the atmospheric water content, and eventually lead to more clouds and more precipitation and those extra clouds will cool the surface wiping out nearly every vestige of the CO2 induced warming.
How do people get grant money to do such totally dumb things ?
Clouds are ALWAYS (climatically) NEGATIVE feedback; and that is the crux of the whole global mean temperature question.
Water as a vapor is a positive feedback warming effect; which also has some negative feedback cooling connecvtions since water vapor absorbs some of the incoming solar spectrum energy (maybe as much as 20%) thereby reducing ground level insolation; but water in liquid and solid form as clouds is always a negative feedback, since more clouds mean higher albedo, and more solar absorptions so lower ground level insolation; and it is this cloud cover ratio (or fraction if you will) that regulates the mean global temperature;
Yes things like CO2, aerosols, cosmic rays, dust, microbes, etc can all affect cloud formation and so modify cloud coverage ; but ultimately the oceans are in total control, and simply adjust the cloud cover to stop whatever temperature changes were happening.
Nasif Nahle (13:51:25) : BRAVO!…In these days, you know, nobody wants wrinkles so they apply botox
It’s snowing, well really it’s dumping snow in huge quantities, upon the Edmonton area! Wow! Snow in mid May!
I compiled a little summary here: http://pathstoknowledge.wordpress.com/2009/05/19/its-weather-and-climate-20cm-of-snow-in-edmonton-area-may-19th-2009/
George E. Smith 10.22.15
A question – is an industrial catalyst a commercial forcing?
“Why do the “corrections” always seem to go one way?”
Because they have an agenda and are liars.
I wonder if ERSST’s negative satellite bias had anything to do with those pesky ARGO buoys which kept showing that the oceans were cooling when any fool knew they were warming cause we have Dangerous Anthropogenic Global Warming.
I wonder what Global temperature site to belive.
I would suggest the site that makes the raw data plus source code available to the interested public.
The experts would then be able to debate the merits of the averaging process and not have to speculate on the politics of the organization.
“Clouds are ALWAYS (climatically) NEGATIVE feedback; and that is the crux of the whole global mean temperature question.”
Nope. Who licensed you to make up your own physical law like that? I have no idea where you live, but those of us who live at temperate latitudes know very well that cloudy winter days are much warmer than clear winter days. So, if winter cloudiness were to increase because of other climate changes, that would be…?
I’ll be interested to see just how you reconcile facts like that with your beliefs.
Fluffy Clouds (Tim L): You asked, “Is there any way to subtract out the biases add in, so we can get an honest answer?”
Could you be more specific? What honest answer are you looking for?
Above, I subracted the ERSST dataset without the satellite data from the dataset with it to try to identify the satellite “bias”.