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1. A Machine Learning Algorithm to Detect and Analyze Meteor Echoes Observed by the Jicamarca Radar

   https://doi.org/10.3390/rs15164051  

   Li, Yanlin; Galindo, Freddy; Urbina, Julio; Zhou, Qihou; Huang, Tai-Yin (August 2023, Remote Sensing)

   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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2. Seasonal and Local Time Variation in the Observed Peak of the Meteor Altitude Distributions by Meteor Radars

   https://doi.org/10.1029/2024JD040978  

   Dawkins, E_C M; Janches, D; Stober, G; Carrillo‐Sánchez, J D; Lieberman, R S; Jacobi, C; Moffat‐Griffin, T; Mitchell, N J; Cobbett, N; Batista, P P; et al (November 2024, Journal of Geophysical Research: Atmospheres)

   Abstract Meteoroids of sub‐milligram sizes burn up high in the Earth's atmosphere and cause streaks of plasma trails detectable by meteor radars. The altitude at which these trails, or meteors, form depends on a number of factors including atmospheric density and the astronomical source populations from which these meteoroids originate. A previous study has shown that the altitude of these meteors is affected by long‐term linear trends and the 11‐year solar cycle related to changes in our atmosphere. In this work, we examine how shorter diurnal and seasonal variations in the altitude distribution of meteors are dependent on the geographical location at which the measurements are performed. We use meteoroid altitude data from 18 independent meteor radar stations at a broad range of latitudes and investigate whether there are local time (LT) and seasonal variations in the altitude of the peak meteor height, defined as the majority detection altitude of all meteors within a certain period, which differ from those expected purely from the variation in the visibility of their astronomical source. We find a consistent LT and seasonal response for the Northern Hemisphere locations regardless of latitude. However, the Southern Hemisphere locations exhibit much greater LT and seasonal variation. In particular, we find a complex response in the four stations located within the Southern Andes region, which indicates that the strong dynamical atmospheric activity, such as the gravity waves prevalent here, disrupts, and masks the seasonality and dependence on the astronomical sources. 

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3. Reassessing the Relationship Between Meteor Radio Afterglows and Optical Persistent Trains

   https://doi.org/10.1029/2025JA034327  

   Cordonnier, L E; Obenberger, K S; Taylor, G B; Holmes, J M; Dowell, J; Vida, D (September 2025, Journal of Geophysical Research: Space Physics)

   Abstract Meteor radio afterglows (MRAs) and optical persistent trains (PTs) are two types of long‐lived phenomena which are occasionally observed following the occurrence of a meteor. Both phenomena are thought to be produced by intrinsic emission mechanisms; PTs have been associated with chemiluminescent reactions between meteoric metals and atmospheric ozone whereas MRA emission arises due to radiation emitted by processes in the meteor's plasma trail. Previous research has identified an association between these phenomena, and proposed a mechanism by which the reactions responsible for PTs could also fuel MRAs. In this work, we investigate said connection using a substantially larger catalog containing hundreds of examples of each phenomenon. Using meteor data from the Global Meteor Network (GMN), we performed a directed search in all‐sky radio images obtained by the Long Wavelength Array (LWA) radio telescope to identify meteors with MRAs. The resulting catalog spanned nearly 2 years and contained a total of 2,887 meteors, with 675 MRA events and 372 PTs. Statistical analyses suggest that the connection between the two phenomena is not as strong as previously supposed. Additionally, we show that the MRA occurrence rates do not have a strong seasonal dependence, meteoroid strength dependence, or preference between meteor showers and sporadics. Interestingly, we find that a meteor's entry angle appears to play a significant role in whether an MRA is observed. 

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4. Derivation of Red Tide Index and Density Using Geostationary Ocean Color Imager (GOCI) Data

   https://doi.org/10.3390/rs13020298  

   Lee, Min-Sun; Park, Kyung-Ae; Micheli, Fiorenza (January 2021, Remote Sensing)

   Red tide causes significant damage to marine resources such as aquaculture and fisheries in coastal regions. Such red tide events occur globally, across latitudes and ocean ecoregions. Satellite observations can be an effective tool for tracking and investigating red tides and have great potential for informing strategies to minimize their impacts on coastal fisheries. However, previous satellite-based red tide detection algorithms have been mostly conducted over short time scales and within relatively small areas, and have shown significant differences from actual field data, highlighting a need for new, more accurate algorithms to be developed. In this study, we present the newly developed normalized red tide index (NRTI). The NRTI uses Geostationary Ocean Color Imager (GOCI) data to detect red tides by observing in situ spectral characteristics of red tides and sea water using spectroradiometer in the coastal region of Korean Peninsula during severe red tide events. The bimodality of peaks in spectral reflectance with respect to wavelengths has become the basis for developing NRTI, by multiplying the heights of both spectral peaks. Based on the high correlation between the NRTI and the red tide density, we propose an estimation formulation to calculate the red tide density using GOCI data. The formulation and methodology of NRTI and density estimation in this study is anticipated to be applicable to other ocean color satellite data and other regions around the world, thereby increasing capacity to quantify and track red tides at large spatial scales and in real time. 

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5. SuperDARN Observations of Semidiurnal Tidal Variability in the MLT and the Response to Sudden Stratospheric Warming Events

   https://doi.org/10.1029/2018JD030157  

   Hibbins, R. E.; Espy, P. J.; Orsolini, Y. J.; Limpasuvan, V.; Barnes, R. J. (May 2019, Journal of Geophysical Research: Atmospheres)

   Abstract Using meteor wind data from the Super Dual Auroral Radar Network (SuperDARN) in the Northern Hemisphere, we (1) demonstrate that the migrating (Sun‐synchronous) tides can be separated from the nonmigrating components in the mesosphere and lower thermosphere (MLT) region and (2) use this to determine the response of the different components of the semidiurnal tide (SDT) to sudden stratospheric warming (SSW) conditions. The radars span a limited range of latitudes around 60°N and are located over nearly 180° of longitude. The migrating tide is extracted from the nonmigrating components observed in the meridional wind recorded from meteor ablation drift velocities around 95‐km altitude, and a 20‐year climatology of the different components is presented. The well‐documented late summer and wintertime maxima in the semidiurnal winds are shown to be due primarily to the migrating SDT, whereas during late autumn and spring the nonmigrating components are at least as strong as the migrating SDT. The robust behavior of the SDT components during SSWs is then examined by compositing 13 SSW events associated with an elevated stratopause recorded between 1995 and 2013. The migrating SDT is seen to reduce in amplitude immediately after SSW onset and then return anomalously strongly around 10–17 days after the SSW onset. We conclude that changes in the underlying wind direction play a role in modulating the tidal amplitude during the evolution of SSWs and that the enhancement in the midlatitude migrating SDT (previously reported in modeling studies) is observed in the MLT at least up to 60°N. 

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