Fun with Thermometers

27 04 2008

A guest post by David Smith

Recently I completed my tenth survey for Surfacestations.org. These surveys are fun, almost like treasure hunts where the clues are good but not always great, thus requiring some ingenuity. Also, the surveyor gets to see areas which may otherwise never be visited. And, they’re for a good cause.

While I found no “poster-child” poor quality sites I did observe an array of siting problems. Some thermometers were near the drip-lines of trees, some next to buildings, one was near a concrete patio, one at a sewage plant, several sat above poorly-drained soil and so forth.

These conditions are less than ideal, obviously. Perhaps more importantly, these conditions can change over time. Trees and shrubs grow and die, ground cover changes, concrete is added (and tends to darken over time), drainage may improve or deteriorate, fences and other construction are added or removed, and so forth. Each of these can subtly change the local temperature, a situation which is especially important if one is looking for changes of a fraction of a degree.

To what extent do these imperfections affect local temperature?  Well, we really don’t know (or if anyone knows they’re not talking!).

So, to make a small and imperfect step in that direction, I’m running a few local experiments. My goal is to examine, at least qualitatively, how local microclimate factors like trees and concrete affect temperature. As you’ll see, my methods are too crude to allow fractions of a degree determinations but I should be able to quantify the magnitudes of the impacts of trees, concrete, etc. Or at least that is my goal.

First, my instruments:

I’m using several temperature detector/recorders (”USB1″) like the gray object shown in the photo. These electronic devices measure and log the temperature to the nearest degree F and allow sampling on various schedules. I use 30-minute sampling.

Note: Interested readers can buy these at:
http://www.weathershop.com/USB1_temperature_logger.htm

At this point I’m testing the hardware and developing my experimental plan. But, I have made a few (literally) backyard tests and I’d like to share one of those. This is to help illustrate the approach and, I hope, stimulate helpful comments from other readers.

This initial run (sort of a beta test) was made in my backyard. It involved two extremes. One is near my garage, above a dark-soil flower bed and landscape bricks. This is near a wooden deck and walkway gravel. This spot gets direct sunlight about 50% of the day.

The second extreme is deep shade, beneath low-tree (crepe myrtle) cover and above thick, semi-tropical shrubbery.This is about twenty feet from sunlight. A photo of the backyard is below, with red boxes marking the two locations:

I also use the temperature readings from an airport/airbase located four miles west of my house. This airport provides professional-grade open-field temperature readings which should reasonably approximate regional ambient conditions.

A representative backyard temperature time series is below:

This shows pretty good agreement between the deep-shade max/min and the local airport open-field max/min, which frankly surprised me. I’d expected the deep-shade readings to show less variability (lower highs and higher lows).

More importantly is the contrast between #1 (sunlight and plant beds) and #2 (deep shade). The #1 spot stayed 5 to 10F hotter at midday than #2 (deep shade) less than 50 feet away (and, as a matter of fact, #1 was 5 to 10 F warmer than the high-quality nearby airport).

Why does this matter? well, suppose a co-op station had slowly drifted, over several decades, from open-field conditions to those found at site #1. What would that do to the apparent trend?  That’s an important question which is at the heart of the surfacestation effort.

This backyard demonstration involved convoluted conditions. There is little chance to untangle the relative contributions of so many variables (bricks, soil, tomato plants, trees, etc). So, my plan is to reduce the number of variables in the tests such that we might be able to make broad conclusions about the relative impacts of trees, concrete, drainage and other factors which may change over time.

This should be fun! Suggestions welcome.