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