UAS and distributed temperature sensing technologies allow atmospheric scientists to observe previously unseen processes. UAS provide high resolution temperature data over large areas at lower costs than traditional tall towers. A study used a UAS equipped with distributed temperature sensing to observe the morning transition period, finding that the sharpness of the temperature gradient decreased by around 4 minutes or 250 meters as vertical mixing weakened the gradient. These new observation methods enable capturing a broader range of spatial and temporal scales than ever before and will lead to new discoveries as atmospheric science moves to more representative locations.

1. UAS and Distributed Temperature Sensing Reveal
Previously Unseen Atmospheric Processes
Chad Higgins, Heather Holmes, Rob Stoll, David Blunck, Ziru Liu, Robert Predosa,
Jason Kelley, Steve Drake, Michael Wing

2. Traditional vs. UAS
• Expensive
• Permanent
• Long Term
• Long installation
cycles
• Low resolution
• ‘representative’
• Inexpensive
• Transient
• Exploratory
• High resolution
• Can create an
ensemble
https://www.climate.gov/news-features/featured-images/tracking-greenhouse-gases-
noaa%E2%80%99s-tall-towers

3. UAV Platform
• Lift capacity: 2kg
• Flight time: ~30 minutes
(depends on conditions)
• Advantages: flight
position is controllable,
‘temporary tall tower’
• Disadvantages: limited
flight times, legal
operation concerns

4. Distributed Temperature Sensing
• Ratio intensity of select
returned wavelengths is
temperature dependent
• Range resolved: 12.5 cm
• Time resolution 1s
• Total range: 5km
900mm

5. Morning Transition
Sharpness of gradient ~4minutes or 250m
Flight #6 Flight #7
Sunrise
LandingandBattery
change

6. • We can capture a broad range of spatial and
temporal scales, more than ever before.
• Morning transition: vertical mixing
weakened grad(T)amplification of unstable
modes
• UAS will allow for new discovery in
atmospheric science as we move to more
‘nontraditional’ locations that are indeed
more representative.
Conclusions

7. Thank You!
http://newag.bee.oregonstate.edu/