flux ratio detection of global thin cirrus...
TRANSCRIPT
Flux Ratio Detection of Global Thin Cirrus Clouds
Eryn Cangi Advisor: Gregory Bothun University of Oregon
Cirrus clouds
Images courtesy NASA & NOAA
Ice crystals High altitude (~15km)
Cirrus clouds & Radiation Budget
1. Ice crystal composition leads to reflection of some sunlight (cooling effect)
2. Large cross-section to thermal infrared leads to absorption and reemittance of radiation (atmospheric heating effect)
Why worry about cirrus?
Estimates of global coverage and any increases are not well known
Knowledge of cirrus coverage is important for climate modeling
Cirrus clouds have so far proven difficult to detect alone/reliably
Other methods
1.38 µm band detection
Scatters off ice, absorbed by liquid water
Images courtesy Robert Simmon, 2013, for NASA & US Geological Survey
False positives
Our approach: astronomical methods
• Sun has a particular ratio of photon fluxes through different filters
• Cirrus clouds reflect sunlight, and so will have similar flux ratios
• Flux ratio: photon counts by position for same object viewed through various bandpass filters
Our approach: Cameras & filters
● On-the-go ● CubeSat
● Installation @ UO
● Rotating filter wheel
Data processing
Take some pictures… ...Then grind through Python / pyRAF scripts with DS9
(this part looks boring on a slide…)
Initial cloud detection
Flux ratios
Take a table of photon counts by location in the image, under one filter…
Take table of counts for same image with another filter…
Compute ratio. Different ratios will correspond to:
Cirrus clouds (same as Sun, remember)
Other clouds
Preliminary results
Good basic imaging with 82a (blue), 11 (yellow), LRGB luminance, and 15 (yellow) (to some extent)
Poor flux with narrowband, IR, other LRGB filters
LRGB luminance 11 yellow IR
Future work
Flux ratio calculations and analysis Code expansion and improvements Collaboration with Portland State CubeSat initiative