A few days with hotter temperatures. Clouds were overhead for much of the weekend, but you can see one cloudless period as represented by the spike of luminosity yesterday afternoon.
We saw lots of interesting weather last week. Had lightning and rain a few days in a row. The pattern continues to emerge that (at this scale) when humidity intersects temperature it signifies rain.
Also, I now have enough light intensity data (both visible and infrared) to plot now. I don’t see any real trends with this new data other than luminosity is a proxy for cloud coverage (temperature is another one, but perhaps situations will emerge where light measurement may forecast rain). Eventually we’ll see the trend where shortening days impact temperature (please, soon!). As always, you get better chart detail by looking at the .pdf chart. Stay tuned as I continue to explain how the data collection system works and what the long term goals for the data is.
MONSOON DATA COLLECTION SYSTEM
I’ve been sharing plots that I automatically generate daily from the sensed data from my Monsoon Data Collection system that sits on my back porch. I figured that there might be interest in what this system consists of and the vision for what this data could provide.
System Bill of Materials:
- Embedded Adventures MOD-1016 Lightning Sensor ((Link)
- Embedded Adventures MOD-1022 Environmental Sensor ((Link)
- Adafruit TSL2591 High Dynamic Range Digital Light Sensor ((Link)
- Raspberry Pi 2 Model B (Link)
- Raspberry Pi 1/2 size breadboard (Link)
- Raspberry Pi Digital I/O Extender (Link)
- Wires, etc., to connect the Raspberry Pi to the I2C Sensors
The Embedded Adventures MOD-1016 is a breakout CCA based on the AS3935 lighting/storm sensor (Link). This part is interesting because it attempts to handle the more challenging aspects of calibration at the factory . This saves the experimenter from writing a lot of calibration code. The MOD-1016 can interface with I2C or SPI, but I typically choose I2C because I’m pretty familiar with the protocol on the Raspberry Pi.
This part also sends interrupts to the Raspberry Pi when something interesting happens. If it senses excess noise in the environment (for example, my RPi case fan that’s acting up), it will send the interrupt so that the RPi can raise the noise floor. It will mask what it determines to be human made disturbers that aren’t real lightning (i.e., the microwave oven!). And finally, it will send an interrupt to inform the RPi when it senses lightning. When requested by the RPi, the sensor will then deliver a unitless intensity value and an estimated distance.
The AS3935 Franklin Lightning Sensor(tm) is made by AMS and advertises detection of cloud to ground and cloud to cloud lightning within a 40km range. The part seems to do what it advertises. The only troubles I have had with it involve interrupts getting “stuck” that force my interrupt service routine to go nuts to service them. This happened once and I powered the system down for a minute, which fixed it.
- Description of other sensors
- Description of the problem being addressed
- Description of the intent for the data
- Discussion of the SW architecture of the system
- Link to GitHub repository
A bit of hot and dry for the last few days. Had a hardware problem with the system that missed some lightning during the rain days. Fixed the issue, now it’s primed to catch the next storms.
Finally have data that reflects a decent rain event. The humidity intersects the temperature for the first time and the pressure is slightly elevated. This is one of the first medium rain events captured on this system. Pretty interesting.
Had much cooler weather yesterday with humidity and pressure up-trend. This coincided with lightning storms in the evening… some passed right over the house.
Storms have abated and the humidity has fallen significantly. Slight downtrend on pressure and uptick in temperature. No hope for clouds and storms today, it appears.
Here’s a 2 week view that captures the storms over the last few days as well as the intense heat wave from the start of the 2 week period. The swing between high and low temperature has flattened out due to the average humidity still being in the 20-30% range, even when the temperature is peaking up over 100.
Very interesting to note the difference in the humidity peaks (less pointed, a few dips at the top) when the storms are in place. Not sure if this is sampling the latent presence of clouds?