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  1. Abstract

    A novel computer vision‐based meteor head echo detection algorithm is developed to study meteor fluxes and their physical properties, including initial range, range coverage, and radial velocity. The proposed Algorithm for Head Echo Automatic Detection (AHEAD) comprises a feature extraction function and a Convolutional Neural Network (CNN). The former is tailored to identify meteor head echoes, and then a CNN is employed to remove false alarms. In the testing of meteor data collected with the Jicamarca 50 MHz incoherent scatter radar, the new algorithm detects over 180 meteors per minute at dawn, which is 2 to 10 times more sensitive than prior manual or algorithmic approaches, with a false alarm rate less than 1 percent. The present work lays the foundation of developing a fully automatic AI‐meteor package that detects, analyzes, and distinguishes among many types of meteor echoes. Furthermore, although initially evaluated for meteor data collected with the Jicamarca VHF incoherent radar, the new algorithm is generic enough that can be applied to other facilities with minor modifications. The CNN removes up to 98 percent of false alarms according to the testing set. We also present and discuss the physical characteristics of meteors detected with AHEAD, including flux rate, initial range, line of sight velocity, Signal‐to‐Noise Ratio, and noise characteristics. Our results indicate that stronger meteor echoes are detected at a slightly lower altitude and lower radial velocity than other meteors.

     
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  2. Abstract

    Simultaneous OH(6,2) and O(1S) nightglow measurements obtained at the Andes Lidar Observatory (ALO) (30.3°S, 70.7°W) from September 2011 to April 2018 have been analyzed to investigate an unusual intensity pattern, that is, O(1S) nightglow intensity enhancement concurrent with OH(6,2) nightglow intensity weakening. We identified 142 nights showing that behavior during the ∼6.5‐year period. The data set comprised of these 142 nights displayed a semiannual occurrence rate with maxima during the equinoxes. A semidiurnal tide fitting applied to the 30‐min bin size monthly averaged data shows that the largest amplitudes of the tide occur in April–May and August–September in both OH(6,2) and O(1S). SABER atomic oxygen (O) climatology near ALO shows higher O densities near the equinoxes, with maximum O densities in March and September at ∼96 km. Lidar temperature analysis suggests that the O(1S) enhancement concurrent with the OH(6,2) weakening is often accompanied by a temperature increase at 96 km and a decrease at 87 km. Simulations using airglow models have also been carried out to investigate the effect of a long‐period oscillation on the OH(6,2) and O(1S) airglow intensities. A sensitivity study has also been conducted to illustrate the effect of the characteristics of a long‐period wave on the airglow intensity patterns.

     
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  3. We present a machine-learning approach to detect and analyze meteor echoes (MADAME), which is a radar data processing workflow featuring advanced machine-learning techniques using both supervised and unsupervised learning. Our results demonstrate that YOLOv4, a convolutional neural network (CNN)-based one-stage object detection model, performs remarkably well in detecting and identifying meteor head and trail echoes within processed radar signals. The detector can identify more than 80 echoes per minute in the testing data obtained from the Jicamarca high power large aperture (HPLA) radar. MADAME is also capable of autonomously processing data in an interferometer mode, as well as determining the target’s radiant source and vector velocity. In the testing data, the Eta Aquarids meteor shower could be clearly identified from the meteor radiant source distribution analyzed automatically by MADAME, thereby demonstrating the proposed algorithm’s functionality. In addition, MADAME found that about 50 percent of the meteors were traveling in inclined and near-inclined circular orbits. Furthermore, meteor head echoes with a trail are more likely to originate from shower meteor sources. Our results highlight the capability of advanced machine-learning techniques in radar signal processing, providing an efficient and powerful tool to facilitate future and new meteor research.

     
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  4. Ground-based temperature measurements at Svalbard, Wuppertal, and Hohenpeissenberg were analyzed to obtain F10.7, Ap index, and Dst index trends. The trends were then compared to those obtained from Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature measurements at the same locations. Trend analysis was carried out for overlapped time periods, full range of available data, and the CO2-detrended full range of available data. The Svalbard meteor radar (SABER) temperature showed a weak (moderate) correlation with F10.7 and a moderate (weak) correlation with Ap and Dst indices. The trends in the Wuppertal OH* temperature compare well with the SABER temperature when a full range of data is used in the analysis. Both temperatures had a similar F10.7 trend with the same level of correlation coefficient. The F10.7 trend in the Hohenpeissenberg OH* temperature compared well with that obtained by SABER, but the former displayed a weak correlation. The Hohenpeissenberg data displayed a very weak correlation with Ap and Dst indices. Our study clearly shows that a longer dataset would better capture trends in temperature, as was evidenced by the results of Wuppertal data. The CO2-detrended temperatures overall showed slightly larger trend values with a slightly better correlation. 
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  5. null (Ed.)
    The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature measurements at low latitudes from 89 km to 97 km were used to derive the F10.7 and Ap index trends, and the trends were compared to model simulations. The annual mean nonzonal (e.g., at the model simulation location at 18° N, 290° E) SABER temperature showed a good-to-moderate correlation with F10.7, with a trend of 4.5–5.3 K/100 SFU, and a moderate-to-weak correlation with the Ap index, with a trend of 0.1–0.3 K/nT. The annual mean zonal mean SABER temperature was found to be highly correlated with the F10.7, with a similar trend, and moderately correlated with the Ap index, with a trend in a similar range. The correlation with the Ap index was significantly improved with a slightly larger trend when the zonal mean temperature was fitted with a 1-year backward shift in the Ap index. The F10.7 (Ap index) trends in the simulated O2 and the O(1S) temperature were smaller (larger) than those in the annual mean nonzonal mean SABER temperature. The trends from the simulations were better compared to those in the annual mean zonal mean temperature. The comparisons were even better when compared to the trend results obtained from fitting with a backward shift in the Ap index. 
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  6. null (Ed.)
    Airglow observations, experimentations, and theoretical studies have significantly advanced our understanding of airglow in recent decades [...] 
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  7. Airglow intensity-weighted temperature variations induced by the CO2 increase, solar cycle variation (F10.7 as a proxy) and geomagnetic activity (Ap index as a proxy) in the Mesosphere and Lower Thermosphere (MLT) region were simulated to quantitatively assess their influences on airglow temperatures. Two airglow models, MACD-00 and OHCD-00, were used to simulate the O(1S) greenline, O2(0,1) atmospheric band, and OH(8,3) airglow temperature variations induced by these influences to deduce the trends. Our results show that all three airglow temperatures display a linear trend of ~−0.5 K/decade, in response to the increase of CO2 gas concentration. The airglow temperatures were found to be highly correlated with Ap index, and moderately correlated with F10.7, with the OH temperature showing an anti-correlation. The F10.7 and Ap index trends were found to be ~−0.7 ± 0.28 K/100SFU and ~−0.1 ± 0.02 K/nT in the OH temperature, 4.1 ± 0.7 K/100SFU and ~0.6 ± 0.03 K/nT in the O2 temperature and ~2.0 ± 0.6 K/100SFU and ~0.4 ± 0.03 K/nT in the O1S temperature. These results indicate that geomagnetic activity can have a rather significant effect on the temperatures that had not been looked at previously. 
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