We’re looking forward to seeing your report. Will you be testing for significance of differences?

It’s really amazing how data accumulate, the challenge presented by their analyses, and what technology allows! Your challenge reminds me of a Marine Ecology professor I knew who did his dissertation on recovery of marine algae communities following El-Nino destruction at UC’s research facility on Catalina Island. He continuously monitored a number of parameters at multiple locations and multiple depths, continuously for several years. Being pre-PC days, he had miles and miles of paper graph/curves accumulate.

After transporting the data rolls back to L.A., packed in sealed ice chests, roped together and attached to floats and flags, he manually (with scissors and friends) cut out all of the graph profiles to quantify (by weight of paper) the areas below the curves for each parameter. What he would have given for a USB-download!

John

Record the temperature for a year, and then study the micro-differences as they are overlaid on an aerial image of the site. Is there a “stream” of higher highs downwind if the ac unit? Can you tell which days the BBQ pit was used? Is there a gradient in nighttime temps as you move away from asphalt and onto the grass?

It would be a big project, but the results would be fascinating, and go a long way towards quantifying the range of some of those errors.

1. What is the resolution of the individual readings? I assume they are digital and if so, what is the smallest reading increment?

2. How accurate are the measuring devices themselves? We appear to be looking at differences at the 1% level or less. Is this realistic?

Seems that the white paints are very nearly the same.

John Andrews

REPLY: Again this is graph is not for analysis, its just to show the extent and general trend.

The NIST calibrated dataloggers have .1 degree F resolution. The differences are there, but of course not visible in this graph. No more questions about this graph please. Wait for the results I’m compiling.

At the scale and resolution which can be posted, little detail can be visually discerned. However, I see a couple of blue Tmins showing below the overlays, and would sure be curious as to your thoughts about that. I assume those are nighttime lows, and I am trying to think of a mechanism which would occasionally cause that. If it were often or always, instrument error would be the culprit, but an occasional lower than low? BTW, I watched (monitored, actually) the cold air drainage out of the hills around Pleasanton, CA one summer, and wondered if there were any of those effects in the location of the test screens.

http://www.iht.com/articles/2008/01/11/america/calif.php

Truth is stranger than fiction

Well that is how a heat sink operates, isn’t it?

This also brings up another sticky issue, is the UHI effect similarly non linear throughout the year? Or worse, non linear through out the day? Or is the UHI bias pretty much dealt with by a simple comparison between a supposedly rural station and subtracting out the rate of change and bias?

REPLY: At this point I’m not saying anything, the analysis is incomplete. This was just a graphic to illustrate the size of data set and the change over season. I had hoped to be further along by now, so I simply provided this as demonstration of work in progress.
Do not draw conclusions from it about UHI or the paint test itself.