Alex English

and 3 more

We present a metric for detecting clouds in auroral all-sky images based on single-wavelength keograms made with a collocated meridian spectrograph. The coefficient of variation, the ratio of the sample standard deviation to the sample mean taken over viewing angle, is the metric for cloud detection. After calibrating and flat-field correcting keogram data, then excluding dark sky intervals, the effectiveness of the coefficient of variation as a detector is tested compared to true conditions as determined by Advanced Very High Resolution Radiometer (AVHRR) satellite imagery of cloud cover. The cloud mask, an index of cloud cover, is selected at the corresponding nearest time and location to the site of a meridian spectrograph at Poker Flat Research Range (PFRR). We use events that are completely cloud-free or completely cloudy according to AVHRR to compute the false alarm and missed detection statistics for the coefficient of variation of the greenline 557.7 nm emission and of the redline 630.0 nm emission. For training data of the years 2014 and 2016, we find a greenline threshold of 0.51 maximizes the percent of events correctly identified at 75%. When applied to testing data of the years 2015 and 2017, the 0.51 threshold yields an accuracy of 77%. There is a relatively shallow and wide minimum of mislabeled events for thresholds spanning about 0.2 to 0.8. For the same events, the minimum is narrower for the redline, spanning roughly 0.3-0.5, with a threshold of 0.46 maximizing detector accuracy at 78-79%.