A guest post by David Smith

This is an update on recent field tests with remote thermometers (see the ”Fun with Thermometers” post for background).

My goal is to quantify, to an extent, the effects of microsite problems (pavement, buildings, trees, etc) on temperature.

In the current test one sensor (”A”) is currently in an abandoned baseball field at least two hundred feet from any paving, tree, structure, etc other than a chain-link fence:

This reasonably approximates a good-quality site, isolated from human microclimate effects.

The other sensor (”B”) has a split personality. On one side is a poorly-drained field while on the other side is an older asphalt parking lot:

When the wind blows from the north this second sensor tends to reflect the characteristics of the soggy field, while a southerly wind brings air from the parking lot.

An aerial view of the two sites (”A” and “B”) is here:

For this update I selected seven days in May in which the skies were mostly clear throughout the day and night. This should maximize any radiative effects on temperature. (Unfortunately, the site is warm, quite humid and windy this time of year, limiting the magnitude of any radiational microsite effects. But, despite this diminished magnitude there are still useful observations to be made.)

Below is a plot of the average temperature of “B” on five clear-sky days when the breeze was from the parking lot and the average of two clear-sky days when the breeze was from the soggy field. I’ve subtracted the temperature of the nearby baseball field (”A”) from these two averages so that the lines show how much warmer or cooler “B” is than “A”. I’ve also slightly smoothed the data.

All seven days were breezy, which mixes air and limits its time over the surfaces, so the effects are probably muted compared to days with less-breezy conditions:

This shows several things. One, when the wind is from the parking lot (red line), the temperature at “B” sensor is warmer than that of the baseball field, night and day. Shortly after sunrise the difference diminishes, presumably due to the higher heat capacity and thus slower warming of the asphalt vs the baseball field. As the sunny day progresses the heat content and temperature of the asphalt rises, reaching a relative peak at “B” in the late afternoon. As the sun sets and evening progresses the temperature of “B” remains elevated but to a smaller extent.

This “parking lot effect” should be noticeably greater this summer, when average windspeed and air mixing diminishes.

The effects when the wind is from the soggy field (blue line) are perhaps even more interesting. The temperature of “B” tends to be depressed vs the baseball field during daylight hours, presumably due to evaporative cooling of the soggy field. The effect is reversed a bit in the late afternoon, possibly when the dry baseball field is radiatively cooling faster than the soggy field.

The soggy field appears to be due to changes in drainage following a yearlong construction project nearby. This change in drainage and probably ground cover was subtle in nature and may have stretched over some time, something which may or may not be detected by a discontinuity algorithm. In this instance it was cooling but my conjecture is that most drainage changes are towards drying, and warming, not wetting and cooling.

These seven days in May are affirmations that it is a bad idea to have sensors in the vicinity of human-induced microsite changes. Changing drainage, repaving the parking lot, aging of the parking lot, changes in parking patterns, etc can all have an effect. The size of the effects in a given year may depend on rainfall, wind anomalies, etc, making it difficult to detect a discontinuity.

More to come.