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Environmental Fluid Mechanics

, Volume 18, Issue 3, pp 683–693 | Cite as

A high resolution measurement of the morning ABL transition using distributed temperature sensing and an unmanned aircraft system

  • C. W. Higgins
  • M. G. Wing
  • J. Kelley
  • C. Sayde
  • J. Burnett
  • H. A. Holmes
Original Article

Abstract

We used an unmanned aircraft system (UAS) to lift and suspend distributed temperature sensing (DTS) technologies to observe the onset of an early morning transition from stable to unstably stratified atmospheric conditions. DTS employs a fiber optic cable interrogated by laser light, and uses the temperature dependent Raman scattering phenomenon and the speed of light to obtain a discrete spatial measurement of the temperature along the cable. The UAS/DTS combination yielded observations of temperature in the lower atmosphere with high resolution (1 s and 0.1 m) and extent (85 m) that revealed the detailed processes that occurred over a single morning transition. The experimental site was selected on the basis of previous experiments and long term data records; which indicate that diurnal boundary layer development and wind sectors are predictable and consistent. The data showed a complex interplay of motions that occur during the morning transition that resulted in propagation and growth of unstable wave modes. We observed a rapid cooling of the air aloft (layer above the strong vertical temperature gradient) layer directly after sunrise due to vertical mixing followed by an erosion of the strong gradient at the stable layer top. Midway through the transition, unstable wave modes were observed that are consistent with Kelvin–Helmholtz motions. These motions became amplified through the later stages of the transition.

Keywords

Boundary layer Atmospheric Distributed temperature sensing Unmanned aircraft system 

Notes

Acknowledgments

We thank John Selker from Oregon State University, and Scott Tyler from University of Nevada for their helpful discussions. The fiber-optic instrument was provided by the Center for Transformative Environmental Monitoring Programs (CTEMPs) funded by the National Science Foundation, award EAR 0930061. Contact Chad Higgins for data used in the analysis. This material is based upon work that is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, under Award number OREZ-FERM-852-E.

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Biological and Ecological EngineeringOregon State UniversityCorvallisUSA
  2. 2.Forest Engineering, Resources, and ManagementOregon State UniversityCorvallisUSA
  3. 3.Biological and Agricultural EngineeringNorth Carolina State UniversityRaleighUSA
  4. 4.Atmospheric Sciences Program, Department of PhysicsUniversity of Nevada, RenoRenoUSA

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