UPDATE: 08/07 2:PM PST MLO responds with improvements to the CO2 data reporting
Approximately 24 hours after I published my story on the January to July trend reversal of CO2 at Mauna Loa, the monthly mean graph that is displayed on the NOAA web page for Mauna Loa Observatory has changed. I’ve setup a blink comparator to show what has occurred:
For those who don’t know, a blink comparator is an animated GIF image with a 1 second delay consisting only of the two original images from NOAA MLO. Individual image URLS for: August 3rd ML CO2 graph | August 4th CO2 Graph
Now the there is no longer the dip I saw yesterday. Oddly the MLO CO2 dataset available by FTP still shows the timestamp from yesterday: File Creation: Sun Aug 3 02:55:42 2008, and the July monthly mean value is unchanged in it to reflect the change on the graph.
[UPDATE: a few minutes after I posted this entry, the data changed at the FTP site] here is the new data for 2008:
# decimal mean interpolated trend
# date (season corr)
2008 1 2008.042 385.37 385.37 385.18
2008 2 2008.125 385.69 385.69 384.77
2008 3 2008.208 385.94 385.94 384.50
2008 4 2008.292 387.21 387.21 384.46
2008 5 2008.375 388.47 388.47 385.46
2008 6 2008.458 387.87 387.87 385.51
2008 7 2008.542 385.60 385.60 385.25
and here is the 2008 data from Sunday, August 3rd:
2008 1 2008.042 385.35 385.35 385.11
2008 2 2008.125 385.70 385.70 384.85
2008 3 2008.208 385.92 385.92 384.38
2008 4 2008.292 387.21 387.21 384.59
2008 5 2008.375 388.48 388.48 385.33
2008 6 2008.458 387.99 387.99 385.76
2008 7 2008.542 384.93 384.93 384.54
Here is the MLO data file I saved yesterday (text converted to PDF) from their FTP site.
Here is the URL for the current data FTP:
ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_mm_mlo.txt
I have put in a query to Pieter Tans, the contact listed in the data file, asking for an explanation and change log if one exists.
UPDATE 08/05 8:55AM PST I have received a response from MLO:
Anthony,
We appreciate your interest in the CO2 data. The reason was simply that
we had a problem with the equipment for the first half of July, with the
result that the earlier monthly average consisted of only the last 10
days. Since CO2 always goes down fast during July the monthly average
came out low. I have now changed the program to take this effect into
account, and adjusting back to the middle of the month using the
multi-year average seasonal cycle. This change also affected the entire
record because there are missing days here and there. The other
adjustments were minor, typically less than 0.1 ppm.
Best regards,
Pieter Tans
UPDATE 08/05 4:03PM PST
I have been in dialog with Dr. Tans at MLO through the day and I’m now satisfied as to what has occurred and why. Look for a follow-up post on the subject. – Anthony
UPDATE 08/06 3:00PM PST
A post-mortem of the Mauna Loa issue has been posted here:
http://wattsupwiththat.wordpress.com/2008/08/06/post-mortem-on-the-mauna-loa-co2-data-eruption/
– Anthony
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We all try not to believe in any “conspiration theory”.
But lets be honest, ok? Ill say it as it is, maybe say what many thinks, but many dare not to say because we all want to appear serious and well balanced:
Take the last hundred “adjustment” we have had in the last years.
I mean adjustments that are making a difference in the debate pro/contra AGW beliefs.
How many of such adjustments happends to favour IPCC/AGW/Alarmists ideas?
I have NEVER seen a single big adjustment done by the alarmists that does not end up being a support for their opinions. NEVER.
But lets say i have missed some, and its only 90 % of their corrections that support themselves.
But if they where honest, adjustment should in 50% of the cases support them and in 50% support the sceptics.
Adjustments are result of bad equipment etc, should not have a tendency to allways support one viewpoint.
How big statistically is the chance that if you through a dice 100 times, that 90% of the times you get 4,5 or 6? Statistically its vertually impossible.
Thats why i believe its fair to finaly conclude: “So many adjustments that just happend to allways support the ones who makes them? Its not statistically possible and thus i find it hard to believe”.
This does not mean that you are a conspirasy freak. It just means that you have the ability to think.
The original data was a “misspeak” which is more than a “misread” but less than a “mislead.”
Misspeaking is common these days.
Any bets on how soon data from satellite surface temperature measurements are put through the Hansenizer?
Although the correction applied to the Mauna Loa CO2 reading for July may be due to a calibration or other error it still does not change the fact that the the Annual January July differential increase for CO2 content for 2008 is the lowest in the 50 years that data for January and July have been recorded. During that period, from 1959 to 2008, the CO2 differential increase was less than 1ppm in 10 years, between 1-2 ppm during 34 years, between 2-3 ppm for 5 years and exceeding 3 ppm in one year that being 1998 when the January July differential recorded was a whopping +3.6ppm. The next lowest year after 2008 was 2004 when the differential was +0.4ppm which is nearly 6 times greater than the 2008 differential increase of +0.07 ppm. This relatively small increase is thus significant although not nearly as much as had the January July differential been negative. Despite high fuel prices I doubt that mankinds CO2 emissions have dropped off significantly in the past 6 months. This clearly suggests that natural forces play a much larger role in regulating the atmospheric CO2 content than do anthropogenic CO2 emissions.
Ed Reid,
What is possible is to collect duplicate or triplicate samples. Alternatively they could do something similar to what they will be doing in Bejing pretty soon which is to divide the single urine sample into two or more subsamples and then if a spurious result is returned by the analysis the the instruments can be rechecked and the duplicate or sub sample can be tested to see if the result can be duplicated or if it is substaintially different suggesting that a calibration or some other type of error occurred.
I think that it is clear that they increased the smoothing of the data. Notice how all of the peaks and vallies in the data all decrease in magnitude from linearity.
The question is, why the sudden need for increased smoothing of the data?
It’s interesting if you use the annual average mauna loa data to compare the annual ppm change in CO2 concentrations to estimates of global population and fossil fuel CO2 emissions in 1977 and 2007. With all three data sets indexed to 1.0 in 1977, you get values of 1.7 for population growth, 1.9 for carbon emissions and 0.8 for the annual PPM increase in CO2. Therefore, carbon energy use almost doubles with population , yet the rate of increase in CO2 decelerates to less than it was in 1977.
A reply from Dr Tans to my earlier email –
—–Original Message—–
From: Pieter Tans [mailto:Pieter.Tans@noaa.gov]
Sent: Tuesday, August 05, 2008 10:37 AM
To: Denise Norris
Subject: Re: Mauna Loa CO2 trend
Denise,
The reason was simply that we had a problem with the equipment for the
first half of July, with the result that the earlier monthly average
consisted of only the last 10 days. Since CO2 always goes down fast
during July the monthly average came out low. I have now changed the
program to take this effect into account, and adjusting back to the
middle of the month using the multi-year average seasonal cycle. This
change also affected the entire record because there are missing days
here and there. The other adjustments were minor, typically less than
0.1 ppm. Too bad for the self-described “skeptics”.
Pieter Tans
Denise Norris wrote:
> Dear Dr Tans,
>
>
>
> I just noticed NOAA upward adjusted the Mauna Loa CO2 for July 2008, but
> I could not find a explanation on the website. As CO2 is of great
> interest to a number of people, is there a specific reason for the
> adjustment? The original value of 384.93 created a little bit of a stir
> amongst the skeptics.
>
>
>
> Thank you,
>
>
>
> Denise Norris
>
——————————
and my response:
—–Original Message—–
From: Denise Norris [mailto:xxxxxxxxx@xxxxx.xxx]
Sent: Tuesday, August 05, 2008 11:37 AM
To: ‘Pieter Tans’
Subject: RE: Mauna Loa CO2 trend
Dr Tans,
Thank you for the clarification of the July data adjustment.
How frequently is the data revised backwards to the extent of 1974? What sort of event would require that sort of adjustment?
I know all this may be a bother, but Mauna Loa is the crown jewel of the CO2 monitoring world and when there is even a minor adjustment, I feel transparency is the best way to head off needless controversy.
Thank you.
Denise Norris
REPLY: FYI part of that response was cut and pasted to me also, except for the last line, and apparently other bloggers got the same response you and I did. – Anthony
Just an observation:
Where the data points meet between the trend line and the seasonal line, the adjustment is far less than between where the lines don’t touch.
““The extent of unfounded skepticism about the disruption of global climate by human-produced greenhouse gases is not just regrettable, it is dangerous…Those who still think this is all a mistake or a hoax need to think again.”
Re-education camp for you, tovarich! Thinking is dangerous! Sit down, shut up and believe what you’re told.
Anthony – perhaps I’m missing something but the latest date’s numbers weren’t the only ones to change based on your blink comparison… watch how many of the spikes appear to suddenly level off – the excuse that the equipment broke for a few days doesn’t hold up across the long term differences in that blink comparison.
REPLY: I spotted that immediately when I made the blink compare, but I’m waiting to hear additional explanations before making my own comments on it.
people will notice…
The explanation has been posted elsewhere, and is simple and proper.
They don’t get daily readings from Mauna Loa, for various reasons. This has been true throughout the entire record. Mauna Loa is designed to measure well-mixed air arriving on the trade winds, and on days when the wind isn’t blowing, they don’t use the measurement to avoid measuring local air, for example. Some days are missing from nearly every month.
For monthly averages, they have been simply averaging the daily readings they get for that month. In July 2008, they only got readings for the last 10 days of the month. Since CO2 levels fall during July, the last 10 days have a lower average than the entire month would have. Apparently, this was the first time they had such a skewed set of daily averages to apply for the month, it made a substantial difference to the monthly average, so they (quite properly) decided to correct it – the average of the last 10 days of July, when there are falling values for all of July, is NOT the appropriate number to use for the average for all of July.
They applied an algorithm to adjust the monthly average to account for which days in the month are missing, and they (again, quite properly) applied it to their entire record. This would make almost no difference in months where the slope of the record is near zero, or where there are missing values near the middle of the month. It will make a bit of difference when missing values are near the ends of the month. And it leads to more accurate values for every month.
Thus the changes you see throughout the entire record.
REPLY: Another new name Lee? What is that, six now?
I have thought about Dr Tans’ explanation for the July adjustment and accept that the original value would have been skewed if only the last 10 days of July had actual data and the rate of change accelerates during the month.
Basically, the July data point is a composite of the prior July data with the last ten days.
Now the interesting point which I just realized is that his ‘change to the program’ then back-filled missing days for the previous 34 years thereby adjusting the values.
This is the sort of adjustment that DQA is suppose to cover.
Bill Illis (07:35:48)
Thank you sir!
That time series graph that is part of the Aug 1 report of NSIDC (Fig 2) is actually showing the data as of 31 July and it clearly shows that as of the end of July the melt rate had slowed.
It’s good to know I wasn’t imagining it.
I missed saving the graph for 1 August (posted 2 Aug), but I have saved images for 2,3, & 4 August, which I’ve saved as (July 31 values saved as August 00) August_00, 02, 03, & 04.
Now, when I flip between Aug 00 & 02, I can clearly see how changes were made several days back into July.
If that response is from a “Dr”, assuming that would be a Ph.D. scientist, his last comment brands him as nothing more than a demagogue, not a scientist. Shame on him.
“Too bad for the self-described “skeptics”.”
Pointless condescension towards people interested in what you’re working on. How classy.
How convenient: “This change also affected the entire record because there are missing days here and there”. How did they figure it out so fast? And if they knew that they didn’t have most of the data of July, why did they go forward with uncomplete data?
This is quite the answer I hear everytime someone has screwed up. They should bring public all the data, and say which days were inserted. It will not resist a statistcal analysis if data was faked.
Ecotretas
The Watergate rule is now in effect.
It is not the crime that is the big problem, it is the cover-up.
Let the “explanations” begin.
This should be most entertaining.
Redneck,
Understand that. However, all the way back to 1974? All retested in 24 hours? Strains credulity!
Also, the “crown jewel” of the AGW crowd is analyzed by a single piece of equipment, which is out of service for 20 days? While I know it is certainly possible, I find it exceedingly strange.
I don’t see how a couple of week’s missing data can cause adjustments going back for 35 years. these algorithms which readjust all the way down the line to “preserve the story” are a bit much. (Even if all calculations are carefully explained and explained–which they are NOT.)
If one make a zillion small adjustments that slowly add up to a large adjustment, one can look up innocently and say the adjustments are very small (i.e., classic “fallacy of the parts”).
This is getting to be like being licked to death by a St. Bernard.
They need to publish their data adjustment algorithm at the daily raw data, so an independent analysis can be done of the algorithm and the effect of missing data points. Seriously, this should not be controversial.
Thank you Dee!
a) “Too bad for the self-described “skeptics”.”
b) EGAD! I hate to sound snippy… but I guess we know how Dr. Tans feels personally about what the data “should” say.
c) As asked before… why did these adjustments need to start right now? I’m certain they’ve had intrument failures/issues in the past, right?
HINT: see a) above.
Anthony,
In the letter sent to you by Dr. Tans, he states,
“The reason was simply that we had a problem with the equipment for the
first half of July, with the result that the earlier monthly average
consisted of only the last 10 days. Since CO2 always goes down fast
during July the monthly average came out low. I have now changed the
program to take this effect into account, and adjusting back to the
middle of the month using the multi-year average seasonal cycle.”
So, correct me if I’m wrong, but what he is saying is that they only had measurements for the last ten days of the month, and the average of these actual measurements was the original 384.93. The new “measurement” adjusts this figure with some kind of interpolation, thus “smoothing” the data. This “smoothing” interpolation now extends back through the entire record. It would be worthwhile to see how this was done.
To make this whole thing more transparent, I think that Dr. Tans needs to release the entire Mauna Loa record of actual measurements, and that they should update their website to post the data on the net in real time. This way people can do their own interpolation to the data without NOAA as an intermediary.
Since CO2 drops in July and the monthly average of actual measurements was 384.93, this implies that the level on July 31st may have been actually lower than 384.93.
Kim
Tom Barney: The Mauna Loa data (as we have seen) is strongly affected by ENSO (which affects uptake by the Pacific ocean), so the difference in ppm increase between 1977 and 2007 may be becuase of and El Nino instead of a LaNina?