I would think it wise for the document to include fiduciary information like the number of days of data on which the data point is based, and also include information on where to obtain the more detailed data.

All in all, I think Dr. Tans seems like a good guy, trying to do a good job, and even doing a decent one. But, the system is not set up as a rigorous source of data for “the whole world” to use! This is probably not Tans’s fault.

Here’s my guess. Their equipment is utterly out of date. The measurements are a combination of using an old piece of equipment, and a lot of manual patches here and there. They don’t have the budget to even buy a backup system! This looks like it’s just one guy doing is best in an old lab.

When I first posted on this thread, I assumed that the measurements were made by a professional lab with the most up-to-date equipment, with stringent calibration procedures, and quality controls. Now I see this is just another academic-like setting, where things are just MADE to look professional, but in fact this is just amateur work at best.

Now look at the way the correction is made. Sure there is an annual cycle, and you can fit it with whatever number of harmonics you want. Dr. Tans talks about “noise” remaining in the data. But that is not noise!!! It IS the data. The CO2 trend and temperature response is what remains AFTER you remove the annual cycle. So if you correct the data by interpolating with the annual cycle, you’ve just LOST the actual physical data. If there was an anomaly in July, we will never know! Whatever analysis of the relationship between the carbon cycle and temperature cannot use the July data. How much of the rest of the data is like that?

So plain interpolation using an average of past values is actually worst than just posting a “blank” month. At least we would know that there are no data for July.

The amateurishness of the whole process is amazing. Sure, Dr. Tans was open in his correspondence, and quite candid, but this only makes them look even worse. To find out that a single guy can suddenly decide to use 6 harmonics instead of four, and modify the historical data at will, that is just flabbergasting! To find out that they could publish data on the Web based on only 10 days, without anyone noticing or raising a flag somewhere along the process, just goes to show that this is NOT a rigorous process.

Without any confirmation from Dr Tans, I think he may have increased the harmonics to refine the automatic adjustments for seasonal variations to deliver a better product. Certainly the changes had near zero effect, so any argument that the data was Hansenized does not hold water (or is full of hot air?).

Without seeing the raw data, I can’t speak to ‘months with large chunks of data missing’ but I suspect that we are talking only a day here and there, unlike July 2008.

I believe that when and if Dr Tans chooses to share more specifics of his methodology, we will have a better understanding of what actually happened.

Dr. Tans first response was a little too specific to describe the changes clearly. I needed a clarification before I assumed something which wasn’t intended.

Do you have any idea on my other questions?

Yes, the correction methodology for the missing July 2008 data was propagated backwards to fill in missing days in the record. Dr Tans has confirmed this in a subsequent email to me. He also changed some of the methodology at the same time.

Dr Tans wrote:

“When I was at it, I made another adjustment to the program. I used to fit 4 harmonics (sine, cosine with frequencies 1/year through 4/year) to describe the average seasonal cycle. I changed that to 6 harmonics.

Therefore, there will be small systematic differences as a function of time-of-year in the de-seasonalized trend. That will be on top of adjustments caused by months in the past during which there were a number of missing days not symmetrically distributed during that month.”

I don’t see a huge issue as the net gain for all of the adjustments is only 0.19 ppmv. Hardly a biasing of the record.

And to clarify the change that was made: The previous interpolation program was inadequate for months with large chunks of missing data, so it had to be changed. The new method caused changes to any month with missing data back to the beginning of our portion of the record. (Is that right?)

I think we have to treat the July 2008 data point with even less then a grain of salt when most the month is missing. Granted the new value may be more accurate then the old value, but then again, maybe not. With 20 out of 31 days missing from the monthly mean, it would strain my trust to just accept it even if the historical data is used to approximate the missing days. One day here and there, I can accept.

I reserve judgment on the value of the July 2008 data point until I see the global July 2008 data.

Stuff happens indeed, but when stuff like this happens, behind the door changes to critical data is wrong. That is why we have DQA.

On the one hand, I can’t get too upset about this as “stuff happens”. On the other hand, I think we’ve learned to treat the Mauna Loa data with a grain of salt– at least on the day it is published!

In the interest of getting closer to the truth, I chose and continue to choose to overlook his observation regarding skeptics. In the larger picture of things, drawing up sides needlessly is silly.

Principles before Personalities and all that rot!

IMHO, this is the sort of stuff the DQA is suppose to prevent/disclose.

—–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

Some instruments — like mercury thermometers– don’t drift much. Often people just rely on the marks on the thermometer as good enough for whatever they are doing. They don’t recalibrate. Other instruments are known to drift, go out of whack etc. This can happen for various reasons.

Obviously, one would like to use an instrument that measured perfectly, and never went out of calibration. But, this is often a practical impossibility. So, judgement is exercised, and some groups deploy an instrument, calibrate before and check afterwards. If the calibration is still “good” on post calibration, the data aren’t changed. If it is terrible the group might flag the data as bad. If it’s shifted a little, people might “correct” the data in some way. In the third case, they need to explain the process so others know what the heck happened.

Since NOAA says they post calibrate, the CO2 monitor is obviously at risk of going out of whack. But we can’t know that for sure until after they post calibrate!