Temperature Recognition Algorithm for the OPAL Mission
Abstract
The Optical Profiling of the Atmospheric Limb (OPAL) mission is a CubeSat project with aims to measure the temperature in the thermosphere between 90 and 140 km. The temperatures are inferred from the characteristic emission lines of molecular oxygen called the O2 A-band (around 760 nm). These temperatures will be used to better understand the evolution of the upper atmosphere during a solar storm and to analyze the temperature signatures of gravity waves. Multiple steps are required to retrieve temperature data from the OPAL satellite. Initially, the data must be deconvoluted from line-of-sight images. Spectral data must then be converted into temperature data via matching observed emissions with those characteristic of the O2 A-band. The software for both the deconvolution and temperature recognition is written in MATLAB. The deconvolution software converts the two-dimensional line-of-sight measurements into a three dimensional distribution by means of the Abel Inversion. The temperature recognition code matches the measures emission curves to the theoretical emission lines-integrated at the spectral resolution of the OPAL instrument, 0.5 nm-to determine the temperature at each altitude in the aforementioned distribution. In the context of developing and testing this software, these two programs will be combined with further programs-together, simulating the line-of-sight measurement of the atmospheric limb by an orbiting satellite-to create a mock mission for the OPAL satellite. Examples of the deconvolution and temperature recognitions will be shown. Uncertainties will be discussed as well as methods of improvement.
Temperature Recognition Algorithm for the OPAL Mission
The Optical Profiling of the Atmospheric Limb (OPAL) mission is a CubeSat project with aims to measure the temperature in the thermosphere between 90 and 140 km. The temperatures are inferred from the characteristic emission lines of molecular oxygen called the O2 A-band (around 760 nm). These temperatures will be used to better understand the evolution of the upper atmosphere during a solar storm and to analyze the temperature signatures of gravity waves. Multiple steps are required to retrieve temperature data from the OPAL satellite. Initially, the data must be deconvoluted from line-of-sight images. Spectral data must then be converted into temperature data via matching observed emissions with those characteristic of the O2 A-band. The software for both the deconvolution and temperature recognition is written in MATLAB. The deconvolution software converts the two-dimensional line-of-sight measurements into a three dimensional distribution by means of the Abel Inversion. The temperature recognition code matches the measures emission curves to the theoretical emission lines-integrated at the spectral resolution of the OPAL instrument, 0.5 nm-to determine the temperature at each altitude in the aforementioned distribution. In the context of developing and testing this software, these two programs will be combined with further programs-together, simulating the line-of-sight measurement of the atmospheric limb by an orbiting satellite-to create a mock mission for the OPAL satellite. Examples of the deconvolution and temperature recognitions will be shown. Uncertainties will be discussed as well as methods of improvement.