Using convoluted distributions to infer auroral brightness during sunlit conditions

Sunlight makes it difficult to measure the aurora. We use data obtained by the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) onboard the Defense Meteorological Satellite Program’s (DMSP) F16-19 satellites to quantify the auroral intensities during sunlit conditions. We use Environmental Disk Radiance (EDR) Aurora data product from the SSUSI-team, where the dayglow is already subtracted. The error in the dayglow-subtraction is proportional to the strength of the dayglow and represents an uncertainty in the observations. We characterize the auroral intensity and the dayglow part of the signal by combining multiple observations during similar solar illumination, and magnetic local time/latitude. By fitting convolutions of symmetric (dayglow-error) and fat-tailed distributions (aurora) on data from many years, it might be possible to separate the signal from the aurora. By comparing this to the regular methods of estimating auroral intensity (mean/median) we will assess the usefulness and importance of this method. We examine the validity of our method by evaluating the fits of the convoluted distributions.