You are correct that there are multiple variables affecting the parking lot thermometer (and the field thermometer for that matter). Cloud cover patterns, sun angle and duration, humidity, instrumentation variability, windspeed, wind direction, day of week (parking patterns), pavement albedo, moisture content of nearby soil, current rainfall, grass height, ground cover type, nearby vegetation and so forth are variables.

The temperature profiles of the seven days in May do not define how parking lot proximity affects temperature. But, they do hint at the complexity of the situation and that antropogenic effects like the parking lot matter.

As you indicated, it will take multiple sensors and extended runs, stretching across seasons, to more-fully characterize anthropogenic effects like parking lots.

These parking lot results are “practice”, as I mentioned at Anthony’s site, wherein I work on techniques and I get a feel for the equipment and data. The reasons I illustrate some of the results are to draw helpful comments from readers and (I hope) to encourage others in other regions to make their own microsite experiments.

And, these practice runs can create intriguing patterns, like the one mentioned in #19.

As an illustration, I have just returned from my drive to work (southern England). After a mile or so of fairly good dry weather the skies suddenly darkened and the rain literally fell like stair rods, to the extent I had to pull over for ten minutes. I continued when the rain had eased off a little. Coming round the edge of the city in this terrible weather there was literally a line in the road and on the other side it was dry and bright with people mowing the lawn. Two miles further on the line of rain reappeared and the rain was of biblical proportions with very severe road flooding. I got home and it was only raining lightly having been dry all day. The rain (not a thunderstorm) straddled both sides of the estuary I drive round and extended for perhaps 10 miles square. I happen to know there are no weather stations in the area so it would go unrecorded. The temp in the rain was 11C, the other side on the dry line it was 19.5C according to the car thermometer.

I don’t know whether satellites can genuinely claim to capture temperature records but it was certain that the area I travelled in would be recorded by the weather station ten miles outside the rain area as being dry and warm. I don’t know if anyone has ever done any calculations on the number of weather stations we need globally to accurately record the huge local varaitions in weather, but I suspect it is many times what we have got!

Tony B

But that’s exactly the point. We don’t know whether site X “contribute to variation in the deltas”.

And we still don’t although there’s data there for a quick look.

The experiment will take at least a year IMO and should contain data from at least two places. Sam U suggests 5 and I tend to agree but that may be expensive. It also needs to be repeated to remove experimental error.

The question would be if the delta between 5 different calibrated and unbiased thermometers a few feet to a few hundred feet apart in an unchanging environment would all be the same delta.

The time period should also be considered. I’d think you’d have to take averages spaced by a year to get really meaningful results.

I have not chimed in here yet as I thought David was getting all the “help” he needed (or could stand). I have not a clue to what DAV is eluding to here

I outlined it in the comments at WattsUpWithThat. Basically, Dave had published the difference between two sensors (one in the parking lot and one on the ball field). Presumably he is claiming to be showing the effect of the parking lot but the parking lot sensor has at least TWO things that could affect its readings. This means he has two variables (at least) with only one equation. That makes the results useless IMHO.

He may have been able to correct for this but AFAIK he hasn’t said so one way or another (I haven’t checked recently). I suggested repeating the experiment using his own sensor.

In the case of the parking lot, you are correct that once the parking lot is established, you may not see much difference in the deltas. The problem, of course, is the jump that occurred when the parking lot was built, which definitely affects the deltas.

Yes, that was my point. I thought it was what the experiment was all about. It has the potential to allow development of better adjustments for changing local environment.

Thank you, that is exactly the type of feedback I was seeking. You gave me a feel for the amount of variation I can expect and that influences the design of the experiment.

To interest a sponsor, I have to show that a better result than nil or uncertain can be (and has been) obtained. Much appreciated.

So what if it’s X degrees higher (or lowere) than the surrounding area? Thermometers in both locations should show the same delta.

The question would be if the delta between 5 different calibrated and unbiased thermometers a few feet to a few hundred feet apart in an unchanging enviroment would all be the same delta.

In order to start on that, you’d have to have 5 unchanging environments about the same distance away from each other. Probably only the best that could be hoped for is 5 that change at the same rate.

So it seems this would be difficult to do as a controlled experiment without a lot of attention to detail.

The point being, the delta around a swampy grass area with changing wind patterns would not be the same as one near a fairly static parking lot, one wouldn’t think. Just the materials!

Then you have the problem I suggested; if a day is at the minimum temp for 1 hour and the maximum temp for 6 hours (or vice versa) does that really tell you anything to get the mean of min/max?

David Smith’s experiment, while otherwise well conducted, has a disconcerting potential flaw that would render the results unusable. It’s not clear that he took the necessary steps to avoid the flaw.

I have not chimmed in here yet as I thought David was getting all the “help” he needed (or could stand). I have not a clue to what DAV is eluding to here. I think David is collecting some temperature data under well measured and observed conditions and not necessarily to provide a basis for a peer-reviewed paper. I think the analysis of these data will provide some interesting insights into what could affect temperature readings on a micro-site scale. I particularly liked the wind influenced temperature and now determining whether that is a micro-site effect.

One can look at the magnitude of micro-site effects prevailing at a given time and then make assumptions on whether that environment occurred in one momentary step (and was or was not detected by looking for break points in the time series) or whether it could have evolved over longer times and making detection of the change more difficult to detect (and adjust for). Anyway it all starts with good and well-controlled tests results.

it really doesn’t matter where the sensors are placed provided that the site itself doesn’t contribute to variations in the deltas (e.g., growing urban development).

But that’s exactly the point. We don’t know whether site X “contribute to variation in the deltas”. However, the assumption by many AGW folks (that mostly it doesn’t affect the deltas) seems to me an unproven hypothesis rather than an observation.

In the case of the parking lot, you are correct that once the parking lot is established, you may not see much difference in the deltas. The problem, of course, is the jump that occurred when the parking lot was built, which definitely affects the deltas.

w.

It’s a completely different matter when you try to use specific temperature readings vs. differentials (e.g. today’s temperature is xxx).

David Smith’s experiment, while otherwise well conducted, has a disconcerting potential flaw that would render the results unusable. It’s not clear that he took the necessary steps to avoid the flaw.