How not to measure temperature, part 23

The picture below is of the USHCN climate station of record for Newport Beach, CA When I first visited this site I did a double take. Then started searching for the “real” temperature sensor.

Newport_Beach_overall480.JPG

Newport Beach closeup480.JPG

I couldn’t believe that NOAA allowed them to use consumer grade equipment. I was sure I just hadn’t located the MMTS sensor. It wasn’t until I looked up the MMS metadata entry for equipment for NB and saw “miscellaneous” listed for rain and temperature sensors, that I began to get concerned.

Newport Beach MMS480.png

I then went back a second time to be sure I hadn’t missed the station, after checking lat/lon on my GPS…because I just didn’t think it possible NOAA would allow a consumer grade sensor in the USHCN dataset. Then I found somebody in the harbor patrol office to ask, and he confirmed that was the station they use to send readings to NOAA.

I was reminded of that famous quote from the movie “Treasure of the Sierra Madre” lampooned in the movie Blazing Saddles; “We don’t need no stinking badges!”. Except, what was playing in my mind then was “We don’t need no stinking homogeneity!”

Note to NOAA: standards exist for a reason.

Apparently the observer wanted wind too, (the wind sensors are on top of the tower, not shown in these pictures)and while I can appreciate that being located at the harbor patrol office, NOAA could have supplied standard equipment in addition to the shiny new consumer grade Davis station. In fact a standard rain gauge and MMTS did exist, but was removed in 1998 in favor of “miscellaneous” equipment.

Now don’t get me wrong, Davis makes a great weather station, but we can’t just replace sensors with other types willy-nilly and have a homogeneously rigorous data set.

But there are other issues too, such as the rooftop proximity, the diesel generator, and the parking lot it sets in the middle of. More pictures available on surfacestations.org

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Jeff
July 16, 2007 9:45 am

Your government dollars at work, to scare you into needing to give more dollars to the government.

Jack
July 17, 2007 2:53 pm

AAAAA how can it be at 10,000 feet elevation if its at the beach??

I R A Darth Aggie
July 18, 2007 11:51 am

Jack, you misread the data:
10.00 FEET (GROUND)

Retired Spook
July 19, 2007 7:31 am

Anthony, I love your site. I’ve been following your project almost from the beginning, although I haven’t felt the need to comment before.
I recently linked to your site in a GW discussion on a conservative political blog, and one of the resident Lefties asked snidely if I had ever heard of “callibration”. I assume he meant that all the badly sited sensors you’ve discovered had most likely been recallibrated to accommodate changes in location or changes to the surroundings. I can’t recall seeing the issue addressed, but it sounds like a red herring to me. Why would you recallibrate a sensor to accommodate a nearby burn barrel as opposed to simply moving the burn barrel farther away? Any comments?

Retired Spook
July 20, 2007 6:29 am

To expand on my comment from yesterday; in further discussion with the same guy, he referred me to this draft report, and particularly to this paragraph:
2.1 Land-based temperature data

Over land, temperature data come from fixed weather observing stations with thermometers housed in special instrument shelters. Records of temperature from many thousands of such stations exist. Chapter 2 outlines the difficulties in developing reliable surface temperature datasets. One concern is the variety of changes that may affect
temperature measurements at an individual station. For example, the thermometer or instrument shelter might change, the time of day when the thermometers are read might
change, or the station might move. These problems are addressed through a variety of procedures (see Peterson et al., 1998 for a review) that are generally quite successful at removing the effects of such changes at individual stations (emphasis – mine) (e.g., Vose et al., 2003 and Peterson, 2005) whether the changes are documented in the metadata or detected via statistical analysis using data from neighboring stations as well (Aguilar et al., 2003).
Subtle or widespread impacts that might be expected from urbanization or the growth of trees around observing sites might still contaminate a dataset. These problems are
addressed either actively in the data processing stage
(emphasis – mine) (e.g., Hansen et al., 2001) or through dataset evaluation to ensure as much as possible that the data are not biased.

I haven’t read the entire 65 page report, but I’ve read enough to be curious as to your response, Anthony.

Evan Jones
Editor
July 21, 2007 7:54 am

I think I’ll go for the “dataset evaluation” option, thanks just the same. (Emphasis mine.)

Retired Spook
July 21, 2007 3:08 pm

That was kind of my thought too, Evan. What I’ve always wondered is, when climate modelers evaluate data sets, do they look at data from sites in close proximity to each other that have completely different data and say, “that’s odd, I wonder what the reason for that is?” Or do they simply weed out the data that doesn’t dovetail with their preconceived notion of what they believe to be happening? Not that anyone would ever admit to doing such a thing.

Evan Jones
Editor
July 21, 2007 7:56 pm

So, let us examine some of the premises and the questions raised by Mr. Watts and others:
A.) UHI offests are calculated from rural site readings.
B.) Although cities haven’t grown too much for a while, many rural sites have undergone a to-be-determined degree of “exurbanite creep”.
Question: Is this discounted? If the claim by some is that cities have not grown much since 1950, does this imply that there is no “exurbanite” adjustment? It would seem prudent to ask.
C.) Said creep may also tend to increase specific, “careless” site violations. (TBD by photo)
So, a potential for a double bias exists. Virtually all to the hot.
And since UHI adjustments are compared with possibly upward-biased rural data, it would seem quite possible that the UHI adjustment is too low (by how much I couldn’t say).
Site survey will help answer these questions.
It would be interesting to know what 100-year trends the well sited “virgin wilderness” stations reveal. (except for “tree creep”?) It’s not a much of a control group, but it’s better than nothing.