Everyone knows about the eclipse that occurred. Many know how mesmerizing the sight of an eclipse is. Many don’t know about the scientific boon that an eclipse is, however. The effect of an eclipse on the temperature is one of the measurable effects of an eclipse done readily at home. Before starting to talk about data, key terms should be discussed.
Temperature: “The measured amount of heat in a place or a body” (Cambridge Dictionary)
To measure temperature, you use a thermometer. Some issues with thermometers are that they increase and affect their environment temperature, but this is negligible if not in subatomic levels.
Relative Humidity: Relative humidity is the ratio of absolute humidity compared to the maximum possible humidity. Absolute humidity is the mass of water vapour over the mass of dry air at a given time and temperature. The maximum possible humidity is dependent on the temperature. Humidity is generally measured in gm/m3.
Dew point: Dew point is the temperature at which the current amount of moisture will saturate the air. As the relative humidity increases, the dew point decreases. An example of this relationship is shown below:
DATA:
Equipment:
For the experiment, we used an Extech RHT10 USB Datalogger (Details at the end). It was basically rubber banded onto a pole, in the shadow of a tree.
The Datalogger (referred hereafter as the Extech) was set to record data every five seconds, and initially set for 8000 samples. 8000 samples would require staying way after the eclipse, so it was ended early, but data was still claimed: a whopping 4594 points.
Times:
The eclipse (in local time) was:
Start: 12:01:59.0
Start of total: 13:30:49.7
Maximum eclipse: 13:32:00.6
End of total: 13:33:11.3
End: 14:57:08.2
Location:
In case it matters, the location for measuring was (roughly) 35* 39’ 20.11” N, 85* 21’ 24.43” W, at Fall Creek Falls State Park, Tennessee. True, it wasn’t an ideal location but it was quite empty, so was great for a viewing ground. Look at the handy data below.
The experiment was conducted in the shade, under a tree in order to prevent the sun from heating up the gauge too much. This doesn’t affect the data too much, because, after all, it’s still a relative drop in temperature and humidity.
Actual Data:
Instead of listing all 4000 and some data points, I’m listing the averages of important groups and specific data (all data linked at bottom).
The average of the first hour was 82.65 degrees, second was 85.25, third was 84.9. After these the eclipse began. These were the three hours of 8:47:42-11:47:42. The first hour to second hour increase was due to the natural warming of the day, and the drop from second to third was due to a cloud. Annoying cloud, worried all the eclipse viewers.
At the beginning of the eclipse (rounded up as it didn’t fall exactly with the measurement cycle) the temperature was 82.78 degrees. The averages of the ten minutes after were 86.71, 88.4, 88.25, 86.1, 85.21, 84.9, 82.65. That was from minutes 0-80 of the eclipse. The next even interval is five minutes after, 85 minutes in, with a temperature of 81.1. The totality began 87 minutes in, and the temperature then was 80.49.
The totality had another drop in temperature. This data is averaging five measurements, starting from total till end. The data is as follows: 80.2, 80.2, 80, 79.93 and 79.8. The data after the eclipse is (in ten minute averages) 79.0, 78.99, 79.77, 80.25, 82.4, 85.5, 88, 88.6, and then 82.5 minutes in for 89.5 and at 84 minutes 89.9. The final two were at that weird offset due to the eclipse having ended.
So the temperature went down! This (to the right, graph 1) is the graph of the temperature change during the eclipse from start to finish in temperature. The jump up was due to a cloud.
The peak temperature (excluding end) was around 1/5th of the way in nearly matches the end temperature of the eclipse.
The next graph includes data before and after the eclipse. This is ten minutes before and after (only data I have for after :p)
As you can see to the left, the graph is much the same, but the peaks and drop are apparent. This reduction, however, may seem like a lot on the graph, but is just an 11 degree drop. This is, of course, Fahrenheit, and not Celsius. I only wish, but I set the Extech to Fahrenheit (sadly). In the graph (through the magic of Excel) the 1-2017 or 2143 is the reading number. The 1 is where the readings for that graph start, with each reading having a five second interval before the other.
This graph doesn’t show the relative humidity and dew point information, however.
Okay. To reiterate, relative humidity is the percent that the air is saturated compared to its maximum possible saturation at the temperature. It has no real purpose but is an indicator of both temperature and moisture. It can be used to predict the weather (obvious reasons), and the higher it is, the higher the moisture in the air.
When does it spike? That happens when clouds are near, or some event happens to interfere with the normal weather, like an eclipse. The eclipse did manage to raise the relative humidity, but as you can see in the next graph, it occurred while the temperature was regaining from its drop. The graph here (below) is the one showing only the eclipse, not before. In it, the Y axis to the left is temperature and the Y axis to the right is relative humidity. As you can see, the relative humidity peaked a bit after the temperature’s own divet. This could have been the Extech, but the increase in relative humidity is supported by prior studies (PMC).
The relative humidity peaked at 77.4% at 14:09:12 (2:09:12). There is another peak visible on the graph. It is due to a cloud (the same one), and actually comes in handy here as it shows how other objects change the relative humidity. The cloud did alter it, but the RH was still greater during eclipse.
I haven’t mentioned the temperature peak, or rather where it was the lowest. This was a 78.8, and it happened at 13:39:37 (1:39:37), 30 minutes before the humidity peak. This is slightly cooler than the air before (slightly from the view of stones and such), but for us, means a lot: ~10 degrees below the highest average temperature.
Of course, who could forget the official Extech generated graph! The one they make is interactive, meaning you can zoom into parts of it, but the one below is all the data.
This is the first of two parts, the second dealing with the corona of the sun. Expect that up some time soon. And, if you are here for the eclipse pictures, here: some photos taken at home (yes, from home and not the internet):
You can see the corona in those!
Sources:
See also:
Extech RHT10 USB Datalogger info: http://www.extech.com/display/?id=14707 (if you want to buy this, Fry’s electronics was selling one a bit cheaper than retail price. Just saying)
Full data spreadsheet: https://docs.google.com/spreadsheets/d/1Y3auIKfQm7SJ85J7XI7XlWx3ALzDmlXipTbxuJxAm6s/edit?usp=sharing
Dhruv, these are really great efforts.
ReplyDeleteThanks for sharing the observations you recorded along with the detailed analysis and nice explanation.
Keep it up!