Climate Audit

EP

Something for the skeptics: wouldn’t it be possible to set up an accurate thermometer nearby to some of these stations where a less biased reading could be made and compared with the official ones? Do we know the times at which readings are officially taken?

Anthony Watts

I just did a look at the MMS data from NCDC, and it shows its always been located at the radio station and the station was located in the same lat/lon since 1951. Assuming the MMS data is correct, it also appears that they were using the Stevenson Screen up to August 2006, when they switched to MMTS temp sesnor seen in the photo.

So something had to change in the environment near the sensor. And here it is in the notes from our survey form:

Curator notes: A/C units were moved from roof of building to current location 5/5/1999.

But that begs the question; If the A/C units were already in place, why didn’t the NOAA/NWS COOP manager insist on a better location when the MMTS was installed?

bernie

#6
I had the same impression plus it looks like a heat exchangers rather than an A/C unit? Is there an HVAC expert on call?

CAS

Has a new trend been identified to be called RHI, or Rural Heat Island?

Paul

OK, this is from a complete novice.

But I have looked at the post on this blog that describes the adjustments made to the surface record (overwhelmingly positive adjustments). Then, I look at all the potentially problematic recording sites and all of those indicate a need to make a negative adjustment (essentially due to obvious development in the form of introduced tarmac increased car traffic, airconditioning units that obviously weren’tthere 50 years ago).

Real Cimate are being complete inenguous when they claim that this work is not of any real import.

Jim Edwards

#6, Joel McDade:

If you’re looking at the units on site, it’s usually pretty easy to tell if they’re completely new installations. I can’t tell from this angle and can’t access the other photos. If a 3-ton unit is replacing a 3-ton unit, people generally use the existing ductwork for packaged units (which these appear to be from this angle…), or the same insulated copper refrigerant lines for split-system condensing units (as seen in the ‘Rain in Maine’ photos a few threads ago…). Ducted units usually have to have a new transition fabricated, so one might see old ductwork connected to new ductwork, or old brown oxidized copper refrigerant lines connected to shiny fittings on the unit if it’s a retrofit. Other clues are fairly old electrical disconnects next to brand new units, or the outline of a slightly differently shaped prior unit on the concrete pad a unit was sitting on. Also look for old, oxidized copper drain lines with new copper fittings within a foot of the unit.

If a hypothetical 3-ton unit from the 1980s were replaced with a new (improved, and warmer! …) 5-ton unit, it would be harder to gauge by looking, b/c most of the ductwork, refrigerant lines, and other facilities would be undersized and replaced with new. Sometimes a clue in these cases would be an old, abandoned electrical disconnect near a new larger one for the new A/C unit. Old refrigerant lines may be abandoned on site, b/c they’re a hassle to remove.

Sometimes when you see two units of different sizes, as you do here, you’ll notice that the smaller, older unit is simply shut off at the electrical disconnect and abandoned in place – so that will tell you quite a lot about the history of the place:

20 yrs ago, they had 4 employees w/ 2 computers and a coffeepot. It was a 2-ton load but they oversized the installation and put in a 3-ton unit.

Over the next 15 years they added 3 dedicated employees who were willing to sacrifice for the cause and work in close quarters. They added a copy machine so they could spread the word on AGW. The heat load went up to 4-tons. On hot days they each melted a glacial ice core.

5 yrs ago the (now) middle-aged director finally sprang for some carbon credits and had a 5-ton unit installed next to the old retired unit. The quarterly fundraising newsletter mentioned that they had stopped using the old A/C unit and were now carbon-neutral.

Jeff C.

This has gone beyond ridiculous. The entire network needs to be surveyed, but we’ve seen enough that it’s clear these aren’t a few isolated incidents.

I wonder if Senator Inhofe’s office has been following this as it seems clear an investigation is warranted. The Coop site operators are unpaid volunteers and I appreciate their efforts and don’t blame them. However, there are highly-paid professionals working for NWS, NCDC and GISS involved that have no legitimate excuse. I’m a Systems Engineer responsible for signing off on the performance of commercial satellite payloads prior to them being placed in-orbit. It is my job not only to analyze the test data, but to sign off on the integrity of the data. If I don’t perform due dilligence, I’m responsible for a potential lost satellite that can cost the company hundreds of millions of dollars. Why is it any different when the taxpayers are footing the bill?

Anthony Watts

I got this letter today:

Dear Mr. Watts,

I fully agree with the points you made in the interview just released on FOX. Your points about the terrible exposures at the majority of NWS Coop sites is inexcusable [the siting, not your points] and calls into question whether the data is worthy of any serious use.

I spent 2.5 years on a sabbatical assignment at NWS HQ [ended on 10/1/06] attempting to help with COOP modernization. I will tell you I ran into a ‘closed shop’ when it came to the modernization. Outside ideas were not welcomed. I tried to bring the best ideas from the Oklahoma Mesonet with me to Silver Spring. Nobody wanted to hear anything about our successes and our standards. I even wrote three documents on site standards and documenting metadata. Furthermore, I developed the interrelated software designed to store and make available all metadata [excepting the names of individuals].

Those documents, written in 2005, are still on the shelf and will go nowhere. The software developed has been turned off. What I gave the NWS was a package better than what we used [at the time] in the Oklahoma Mesonet – but the Mesonet since taken advantage of the developments made for the NWS.

I say: KEEP IT UP.

[name withheld for privacy reasons]

Bill F

More importantly, if all of the stations trying to measure temperature are handicapped by having MMTS units with short cables on them that prevents them from being placed any significant distance from a building…then we should assume that ALL of the units will suffer from the same types of biases documented by Anthony’s work so far, until evidence from specific sites proves otherwise.

Jeff C.

From the NWS San Diego website (http://www.wrh.noaa.gov/sgx/cpm/temperature.php?wfo=sgx)

“Currently, the MMTS requires a cable to connect the sensor with a display. Future plans are for wireless displays. This would eliminate many of the problems associated with cabled systems.”

David Smith

Re #20 The co-op observer I spoke with in Liberty, TX expressed surprise and mild amusement at the MMTS placement at his site. For many years he walked a long distance in all weather to take readings in the Stevenson box, presumably because sensor distance was important, then when MMTS and indoor display come along they place the sensor just a few steps outside his back door.

Those of us who live in areas with grass and light wintertime frost know that proximity to structures makes a difference in frost amount. Generally the grass within 15 feet of a house or tree gets no frost while the farther from the house or trees one goes, the greater the frost. Locating MMTS closer to structures similar to what I’ve seen in the photos would, in my estimation, raise the overnight minimum temperature by some amount. It may only be tenths of a degree, but that’s big enough to impact a climatological record.

I wonder what the outrage would be if drug makers had a similar lack of quality control in their efficacy and no-harm trials. It’s simply amazing.

Bill F

Anthony, I am just guessing, but I suspect that the MMTS units were probably sent out with a standard cable length (probably very short, based on a competitive bid from a government supplier). Getting a longer cable probably meant a special request or having to fill out extra paperwork, and it is doubtful that the people doing the installations felt like doing that extra level of effort…especially if it would mean they had to dig a longer trench to bury the cable.

Sam Urbinto

#3: Another reading might tell us something. (impromptu experiments by some here have shown it does change radically depending on where the thermometer is) But you’d really have to set up an identical setting, change 1 variable, and measure it over time. Then put that back and change a different variable, etc. (Which is rather what the paint test is like if it’s still going on.) While certainly, another sensor in a different setup that’s “better” could be used to see if the anomaly is different, but why not just make the site better? And that still does nothing for the historical record but it would show if indeed the siting makes a difference in the anomaly. Which seems to be obvious that it would. But not that important.

The goals (and/or byproducts) of this project though seem to me to be 1. Photograph the stations so as to begin a photographic record. 2. Identify which sites do not meet the standards. 3. Identify which stations may be contaminated and remove the data or improve the station or both. 4. Prove or disprove the notion that this is a high quality network. 5. Develop a baseline by which to integrate the old data into whatever the CRN produces. 6. Develop a baseline by which to determine the sitings of the CRN network. And so on. It seems that there are not enough datapoints yet to do many of these things, but the goal is not to determine how much of an error there is or what exactly comprises it.

My train of thought is this: If there are published standards on site settings and audit requirements for data validation etc, there is a reason those standards exist. To ensure the data is meaningful, because it is indicitive and accurate. If a station does not meet those standards, that is prima facie evidence the data is not to be trusted. The requirement is not to prove that the data is good or bad, that it should be trusted or not; the requirement is to point out the standards are not met, therefore the station should either be improved or the data ignored.

Put another way, it is not anyone’s “job” to prove the data is not good, nor why; it’s who is collecting the data’s job to prove the data is good. The only way to prove it’s good is not to provide adjustments that may or may not be correct, not to explain why we need adjustments, not to say “Well the site is supposed to reflect some other area so that’s why it’s there”, not to question the motives or sanity of the people pointing out your failure to meet the standards, or any other similar thing. The way to “prove” it’s good is by having it meet the exiting standards in place that are there to ensure the data is good.

That rule of big numbers thing that somebody may bring up; I don’t care how many “guesses” as to what the temperature is at a given spot, you won’t get any degree of accuracy in the “measurements” unless you have a device to measure them and measure them down to two decimals of precsion if you’re going to be tracking them down to one. Has anyone done any experiments to see what’s the best guess anyone’s ever done on the ambient temperature at their hand or ears or elbow or forearm etc and seen how close the best at it is?

Lastly. I’m not a skeptic. I don’t think most people here are. We just want to know what is acutally going on. I’m not skeptical of anything. I am curious as to what the answers are. I don’t care what they are. I just want them.

Sam Urbinto

The trick is to find, having a history,

1. Good stations (meet standards)
2. Those that are dispersed somewhat equidistant as well as providing good coverage (indicating that the coverage is then, well, good coverage)
3. Are free from unnatural (not of nature) influences on the temperature (e. g. no airport tarmac)

Evan Jones

Re 10 & 18

That principle only applies where there is no constant bias (all in the same direction).

What’s going on here is that I am wearing elevator shoes (the microsite/exurban bias). So the 100 folken who’re estimating my height will have a 2″ bias throughout, and they’ll come out of it roughly 2″ too high–no matter how many are doing the estimating.

Naturally, the more that do the estimate, the greater the odds are they’ll come out closer to–exactly–2″ too high.

But it will still be 2″ too high!

bernie

#22 & #31:
Evan and Barry:
I absolutely agree: There are two issues precision and accuracy. The systematic bias you mention is an issue of accuracy: Are we measuring the right thing, my height or my height in 2″ heels. The question of how a rough measure of temperature, i.e., nearest degree, can produce trends measured in hundreths of a degree per year is about precision and the power of multiple estimates. Ian’s comment (#10) was about precision.

To pursue the height analogy: We have people trying to estimate the average height of humans, where some are measuring people in Vietnam, some in Holland, some are measuring men, some are women, some are measuring 10 years old, some are 25 years old and some are 90 years old, and of course some are wearing heels, some platforms, some are wearing flip flops. However, all those doing the estimation were told to measure men, 25 years old and wearing no shoes using a standard tape measure and to keep detailed records of where, when and who exactly they measured. They simply have not followed instructions!

gdn

Accurate multiple estimates to the nearest degree can increase your certainty that the temperature is indeed between a range of plus or minus half a degree, but how can it possibly tell you more? …significant digits and all that.

I can see how you might detect an apparent warming trend within that, but you would only be able to say that it was smaller than a degree, or greater than a degree (or two, three, four), right? Given that the readings were subjective, it could be even less certain than that.

As I recall, there was a big todo a few years back about average human body temperature and how it wasn’t 98.6F, but was 37C. 37C = 36.5 to 37.5; 98.6 = 98.55 to 98.65.

As for the USHCN stations, some of them appear to have been biased by as much as 4C in single episodes (of induced bias). If one in five stations showed that level, it’s pull the whole network off by .8C. If looking at the shift over a decade, it’d only take one in fifty stations to have that effect. That’d only be 24 stations.

Magnus Andersson

Just a Ot comment. I hope they got good fans around the termometers outside the city of Sundsvall. About plus 5 degree Celsius and just a bit snowy today. An image and an article:

http://www.aftonbladet.se/vss/nyheter/story/0,2789,1129554,00.html

The AGW alarmism goes on in Sweden anyway. Our prime minister (who I voted for) has dropped all other questions he sais… 😛 (pure insanity)

Dan Hughes

re: #36

Thanks for the heads up Steven. Could that be limited to 100 estimates of the exact same property? Does it apply to measurement of the temperature at the same location but at different times? Do you have a handy reference for us? I have John Mandel, The Statistical Analysis of Experimental Data, John R. Taylor, An Introduction to Error Analysis and F. B. Hildebrand, Introduction to Numerical Analysis. An example calculation and analysis would also be very helpful.

Steven B

Dan,

It’s not necessarily limited to the exact same property, but it gets more complicated for other cases. It’s just a matter of maths with random variables. The variance of a sum of random variables is the total of all the numbers in their joint covariance matrix – whether the random variables estimate one quantity or many. If you take the mean by dividing the total by n, the variance of this mean is divided by n^2. All that matters is adding up random variables and dividing by a constant, but in context it wouldn’t make much sense to be averaging estimates of different quantities. (If what you’re talking about is the fact that the actual temperature is different at each physical location, that’s OK. If you average these different values to get an estimate of the average global temperature, the average of the errors in them is still supposed to be zero, and our variance calculates the variance in that average.)

For temperatures at different times you’ll commonly get a more complicated covariance structure. Observations close together in time will be more strongly correlated than those far apart. (To some degree, this applies in the spatial case as well.) Depending on whether this decays to zero and how fast, you can get convergence of the mean, but it will be a lot slower than you expect.

In the other thread I give a link to a reference. This quotes the only bit of this argument that isn’t derived from perfectly standard properties of variances, which is the fact that the variance of a sum of correlated data is the sum of all the elements of the covariance matrix. Every stats book I’ve come across always assumes the special case of perfect independence. When I first wanted the result myself, I had to work it out from first principles; it involves some messy algebra, but is pretty straightforward as maths goes. It seems like it should be a standard result, but it’s rare to even find it simply quoted (as my linked reference does) let alone derived.

If you check my Milestone post, you’ll see the formula when the covariances are constant off diagonal is Var(y-bar) = (r +(1-r)/n)Var(y_i) where y is the data being averaged, r the cross-correlation coefficient, and n the sample size. So if r is 0.001, and Var(y_i) is 0.25, then the average of 100 points will have variance (0.001 + 0.999/100)*0.25 = 0.01099*0.25 ~= 0.0025 which gives an accuracy about ten times better. But if we increase the sample size to a million points, we get (0.001 + 0.999/1000000)*0.25 = 0.001000999*0.25 ~= 0.00025 which gives an accuracy only three times better, even though the naive prediction would be that it should be 100 times better. Increasing the sample size any more will make virtually no difference to the accuracy of the average.

Obviously, I don’t know how independent temperature measurements actually are. It would take a detailed knowledge of the entire measurement process to even make a guess. If you’ve got a huge correlation, around 0.1, then those hundredth of a degree accuracies are in major trouble. If r is down around 0.001 as in the above example, then it’s probably not an issue in the situation under discussion. But if you think about how temperature anomaly (as opposed to the mean temperature) is calculated, how likely do you think it is that the correlation is so small?

My apologies for the length of the post. I can do a more detailed discussion of any gaps tomorrow if people ask for it, and if Steve M doesn’t object, but I hope that with these pointers it should be possible to leave it as ‘an exercise for the student’. 🙂

Eli Rabett

You might go read the station history. There is a problem but it is almost certainly not the air conditioner or the building