Passing the 1000 mark


Another parking lot being measured for climate change: Newport, TN

My project has reached an important milestone.

With the submission of #222, Lexington, VA, submitted by John Goetz, we are now below the 1000 mark (out of 1221) stations left to survey. It was a 3 -way race to #222 between power surveyors John Goetz, Kristen Byrnes, and Don Kostuch.

Thanks to ALL of the wonderful volunteers for helping to reach this important benchmark! We currently stand at 231 surveyed stations and 990 left to go.

I still need help in the midwest and the south, particularly Kansas, Nebraska, Montana, the Dakotas, Oklahoma, Mississippi, and Alabama. If you live in the areas want to make a lasting contribution to science, please visit and sign up as volunteer. Its easy to do, and it makes for a fun science learning experience.

To see more weather stations like this one, see my “How not to Measure Temperature” series on this blog. This is only a small sample of the 231 surveyed to date, but it will give you an idea of the problems that have been seen so far.

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Russell Steele
July 28, 2007 12:15 pm

Anthony, congratulations! You have made an important contribution to climate science by launching this wikiclimatology project. The collaboration of a few dedicated volunteers will have a major impact on the public view of global climate change, especially if the reported change is measured by a broken data collection system.

July 28, 2007 12:49 pm

Russ, as the very first volunteer for the project, you deserve special recognition and thanks.
Russ has surveyed a number of important stations in California, such as Lake Spaulding, and will soon be adding Nevada and Idaho stations to the list.
Thank you Russ, for your generous contribution of time and expertise.

July 28, 2007 9:37 pm

Would it be too much to ask to have daily/weekly updates of counts of well sited stations, somewhat poorly sited stations, and poorly sited stations?

July 28, 2007 10:16 pm

I have held off drawing any conclusions on the study until we got a significantly large and well distributed sample. Now that we are nearly at 20% of all 1221 stations, we will start keeping a running total.
Look for it in about a week.

Evan Jones
July 29, 2007 5:47 am

Great! Are you going to use them newfangled 1a-5c ratings?
(I assume you already have Central Park in NYC. If not, maybe I can run it down for you. Mon general informs me she’s seen it; it is located on a roof enclosure atop Belvedere Csstle.)

July 29, 2007 7:45 am

We’ll be using the CRN (Climate Reference Network)guidelines as written about here:
These are NOAA’s own published standards.
We do have NYC central park already in the database:

July 29, 2007 12:02 pm

When I began studying engineering, a professor once said that you can become very precise in your imprecision (i.e., calculating a number to 6 decimal places when the number itself is way off from reality). It seems that the (assumed) highly precise MMTS equipment used here, even if technically of high quality, is producing grossly imprecise results due to their placement. GIGO.

Evan Jones
July 29, 2007 12:12 pm

Great! And thanks. I look forward to it.

Milton Scritsmier
July 29, 2007 7:37 pm

Anthony, you’ve done great work leading the charge on pointing out possible legitimate siting issues without pushing an agenda one way or the other. However, do you know of anyone taking the next step of finding out just what the magnitude of these siting biases may actually be? I’m talking about putting stations within yards of each other, siting one over asphalt, one near asphalt, one over grass, one near external A/C units, etc. and just tracking them over time to see if their temperature changes are the same. An actual experiment of this type may not answer all the questions about siting but it would greatly reduce the uncertainty.
And maybe somebody has already pointed this out, but an overall siting bias that causes a higher temperature reading than the actual doesn’t necessarily spell the end of global warming. Let’s say we are measuring an overall 1 degF increase in mean temperature here in the mainland US from these stations. And let’s suppose we discover that siting issues have caused this average to be 0.2 degF higher than it should be. Then measurements such as the melting of glaciers here in the US (which are done independent of temperature readings) have been happening at a mean temperature increase of only 0.8 degF, not 1 degF! Wouldn’t that mean we should be even more concerned about global warming effects? On the other hand, a siting bias of (say) 1.2 degF higher would mean something else besides global warming is causing changes in our environment.
There are few issues in climate change that can be easily resolved by observation, starting with what the climate would be like without us around. That’s a big reason why the issue is so heated. We are lucky, however, that much of the uncertainty over the siting issue can be removed by experiment. It seems to me that all any *honest* person on either side of the argument should care about is just getting the facts.

Evan Jones
July 30, 2007 2:01 pm

Sounds reasonable to me, although it would involve a certain degree of work and expense. (Approve of the last sentence.)
BTW, any word on the latex paint vs. whitewash experiment?

David Walton
July 31, 2007 1:15 pm

Congratulations and add to that two more congratulations. Occupying the #1 slot in an Anthony Watts search of Google News —
Watts rattles warming theologians
…and a global warming watts search reveals a new Paradise Post column in the #1 slot —
Cause of global warming is still undecided

August 1, 2007 3:17 pm

I’ve really got to get on this. I’m in north Alabama and am planning on visiting several stations within a couple hours drive in AL, TN, MS and possibly GA.

August 22, 2007 5:12 pm

This auditing of stations used to create the purported “surface temperature record” is going very well.
One of the other articles of faith of the “Killer AGW” lobby is the notion of a steep decline in Arctic sea ice extent. How real is it, or, is it another case of suspect data fed into a “data muncher” algorithm and out comes the “expected” result?
Here is something to whet your appetite:

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