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Synthesis and Operation of Fluorescent-core Microcavities for Refractometric Sensing
Published on: March 13, 2013
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A simple approach for estimating the refractive index structure parameter (Cn²) profile in the atmosphere
Optics Letters
|September 15, 2015
Summary
We present a new, inexpensive method to estimate atmospheric turbulence (Cn2) profiles using temperature soundings. This approach effectively identifies turbulent layers and is validated by Mauna Kea field data.
Area of Science:
- Atmospheric physics and optics
- Remote sensing and turbulence modeling
Background:
- Accurate estimation of atmospheric turbulence, quantified by the refractive index structure parameter (Cn2), is crucial for optical astronomy and atmospheric studies.
- Existing methods for Cn2 profiling often require complex instrumentation or high-resolution atmospheric data, limiting their widespread application.
Purpose of the Study:
- To develop and validate a physically-based, computationally inexpensive approach for estimating Cn2 profiles in the lower atmosphere.
- To demonstrate the capability of the proposed method to capture layers of significant optical turbulence using readily available temperature profiles.
Main Methods:
- Utilized the Thorpe scale as a metric for the turbulence outer scale.
- Developed a novel Cn2 estimation technique requiring only coarse-resolution temperature profiles (soundings) as input.
- Validated the approach using observational data from a field campaign conducted on Mauna Kea, Hawaii.
Main Results:
- The proposed method successfully estimated Cn2 profiles from coarse temperature soundings.
- The approach demonstrated an intrinsic ability to identify and characterize layers with high optical turbulence.
- Validation against field campaign data confirmed the efficacy of the new estimation technique.
Conclusions:
- A physically-based, computationally inexpensive method for Cn2 profiling using temperature soundings has been successfully developed and validated.
- This approach offers a practical solution for estimating optical turbulence, particularly in identifying turbulent layers, with potential applications in adaptive optics and atmospheric monitoring.
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