PS water vapor analysis, Nov 2014
First update, 2015 Jan 12, Tyler St. Germaine
I have written a code in Python that runs through a directory of fits files, isolates the spectrum of Polaris, and performs PWV analysis on it.
Sample of Images and Spectra
This is a set of what some of the typical spectra look like in the data set:
...
- This is an image where the filter wheel has the spectrum "chopped up", making it not useful for analysis of absorption features.
- I'm not sure what's happening in images like these. It seems the spectrum just gets cut off halfway, not due to running off the CCD.
- Also a little unsure of what happens here. The background sky seems to be drowning out the starlight, perhaps it's getting too close to sunrise? It also looks like there may be a cloud?
When the code runs through all the images, it throws out data that looks like the bottom three cases above, and keeps only the "good" images.
Finding the absorption features
As seen in the spectrum in the case of the "good" image, after isolating the entire Polaris spectrum, the code singles out the six points on the spectrum corresponding to the following features:
| Feature | Wavelength (nm) |
|---|---|
| O2 B | 683 |
| O2 A | 762 |
| H2O | 723 |
| H2O | 822 |
| H2O | 909 |
| H2O | 946 |
To convert the spectrum from pixels to nm, it finds the O2A and O2B features, uses those two as known wavelengths, and calibrates the rest of the spectrum given those two points.
To-do, as of 1/12/15
- Measure equivalent widths of the six features, analyze over time
- My analysis so far has only been on a subset of all the data, due to the difficulty of not having access to the external drive on my mac. To do: get another external drive to reformat the original drive, allowing me to analyze all the data at once
- Cosmic rays may throw off the way my code analyzes the images. Matt recommended I use cosmics.py to simply remove them from the image before analysis.
- Temperature data is stored in the headers of the files. Investigate how the quality of the image changes versus time or temperature (e.g. focal length)