Paper
5 May 2012 Automation of Cn2 profile extraction from weather radar images
Lee R. Burchett, Steven T. Fiorino, Matthew Buchanan
Author Affiliations +
Abstract
A novel method for measuring the structure constant of the atmospheric turbulence on an arbitrary path has recently been demonstrated by the Air Force Institute of Technology (AFIT). This method provides a unique ability to remotely measure the intensity of turbulence, which is important for predicting beam spread, wander, and scintillation effects on High Energy Laser (HEL) propagation. Because this is a new technique, estimating A novel method for measuring the structure constant of the atmospheric turbulence on an arbitrary path has recently been demonstrated by the Air Force Institute of Technology (AFIT). This method provides a unique ability to remotely measure the intensity of turbulence, which is important for predicting beam spread, wander, and scintillation effects on High Energy Laser (HEL) propagation. Because this is a new technique, estimating Cn2 using radar is a complicated and time consuming process. This paper presents a new software program which is being developed to automate the calculation of Cn2 over an arbitrary path. The program takes regional National Weather Service NEXRAD radar reflectivity measurements and extracts data for the path of interest. These reflectivity measurements are then used to estimate Cn2 over the path. The program uses the Radar Software Library (RSL) produced by the Tropical Rainfall Measuring Mission (TRMM) at the NASA/Goddard Flight Center. RSL provides support for nearly all formats of weather radar data. The particular challenge to extracting data is in determining which data bins the path passes through. Due to variations in radar systems and measurement conditions, the RSL produces data grids that are not consistent in geometry or completeness. The Cn2 program adapts to the varying geometries of each radar image. Automation of the process allows for fast estimation of Cn2 and supports a goal of real-time remote turbulence measurement. Recently, this software was used to create comparison data for RF scintillation measurements. In this task it performed well, extracting thousands of measurements in only a few minutes.using radar is a complicated and time consuming process. This paper presents a new software program which is being developed to automate the calculation of Cn2 over an arbitrary path. The program takes regional National Weather Service NEXRAD radar reflectivity measurements and extracts data for the path of interest. These reflectivity measurements are then used to estimate Cn2 over the path. The program uses the Radar Software Library (RSL) produced by the Tropical Rainfall Measuring Mission (TRMM) at the NASA/Goddard Flight Center. RSL provides support for nearly all formats of weather radar data. The particular challenge to extracting data is in determining which data bins the path passes through. Due to variations in radar systems and measurement conditions, the RSL produces data grids that are not consistent in geometry or completeness. The Cn2 program adapts to the varying geometries of each radar image. Automation of the process allows for fast estimation of Cn2 and supports a goal of real-time remote turbulence measurement. Recently, this software was used to create comparison data for RF scintillation measurements. In this task it performed well, extracting thousands of measurements in only a few minutes.
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Lee R. Burchett, Steven T. Fiorino, and Matthew Buchanan "Automation of Cn2 profile extraction from weather radar images", Proc. SPIE 8380, Atmospheric Propagation IX, 83800I (5 May 2012); https://doi.org/10.1117/12.919198
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KEYWORDS
Radar

Reflectivity

Turbulence

Scintillation

Atmospheric propagation

Data processing

Laser beam propagation

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