The Super Dual Auroral Radar Network (SuperDARN) is a network of High Frequency (HF) radars that are typically used for monitoring plasma convection in the Earth's ionosphere. A majority of SuperDARN backscatter can broadly be divided into three categories: (a) ionospheric scatter due to reflections from plasma irregularities in the E and F regions of the ionosphere, (b) ground scatter caused by reflections from the ground/sea surface following reflection in the ionosphere, and (c) backscatter from meteor trails left by meteoroids as they enter the Earth's atmosphere. Due to the complex nature of HF propagation and mid‐latitude electrodynamics, it is often not straightforward to distinguish between different modes of backscatter observed by SuperDARN. In this study, we present a new two‐stage machine learning algorithm for identifying different backscatter modes in SuperDARN data. In the first stage, a neural network that “mimics” ray‐tracing is used to predict the probability of ionospheric and ground scatter occurring at a given location along with parameters like the elevation angles, reflection heights etc. The inputs to the network include parameters that control HF propagation, such as signal frequency, season, UT time, and geomagnetic activity levels. In the second stage, the output probabilities from the neural network and actual SuperDARN data are clustered together to determine the category of the backscatter. Our model can distinguish between meteor scatter, 1/2 hop E‐/F‐region ionospheric as well as ground/sea scatter. We validate our model by comparing predicted elevation angles with those measured at a SuperDARN radar.
The Super Dual Auroral Radar Network (SuperDARN) was built to study ionospheric convection and has in recent years been expanded geographically. Alongside software developments, this has resulted in many different versions of the convection maps data set being available. Using data from 2012 to 2018, we produce five different versions of the widely used convection maps, using limited backscatter ranges, background models and the exclusion/inclusion of data from specific radar groups such as the StormDARN radars. This enables us to simulate how much information was missing from older SuperDARN research. We study changes in the Heppner‐Maynard boundary (HMB), the cross polar cap potential (CPCP), the number of backscatter echoes (
- Award ID(s):
- 1934997
- PAR ID:
- 10366903
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Space Physics
- Volume:
- 127
- Issue:
- 2
- ISSN:
- 2169-9380
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract -
The Super Dual Auroral Radar Network (SuperDARN) is an international network of ground-based, space weather radars which have operated continuously in the Arctic and Antarctic regions for more than 30 years. These high-frequency (HF) radars use over-the-horizon (OTH) radio wave propagation to detect ionospheric plasma structures across ranges of several thousand kilometers (km). As a byproduct of this technique, the transmitted radar signals frequently reflect from the Earth's surface and can be observed as ground backscatter echoes. The monthly files in this dataset contain maps of daily ground backscatter observations from the Kapuskasing (KAP) SuperDARN HF radar binned onto an equal-area 24 km grid. The KAP radar is located in Ontario, Canada (49.39°N, 82.32°W) and is operated by Virginia Tech (Principal Investigator: J. Michael Ruohoniemi, mikeruo@vt.edu) with funding support from the National Science Foundation.more » « less
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The Super Dual Auroral Radar Network (SuperDARN) is an international network of ground-based, space weather radars which have operated continuously in the Arctic and Antarctic regions for more than 30 years. These high-frequency (HF) radars use over-the-horizon (OTH) radio wave propagation to detect ionospheric plasma structures across ranges of several thousand kilometers (km). As a byproduct of this technique, the transmitted radar signals frequently reflect from the Earth's surface and can be observed as ground backscatter echoes. The monthly files in this dataset contain maps of daily ground backscatter observations from the Goose Bay (GBR) SuperDARN HF radar binned onto an equal-area 24 km grid. The GBR radar is located in Labrador, Canada (53.32°N, 60.46°W) and is operated by Virginia Tech (Principal Investigator: J. Michael Ruohoniemi, mikeruo@vt.edu) with funding support from the National Science Foundation.more » « less
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The Super Dual Auroral Radar Network (SuperDARN) is an international network of ground-based, space weather radars which have operated continuously in the Arctic and Antarctic regions for more than 30 years. These high-frequency (HF) radars use over-the-horizon (OTH) radio wave propagation to detect ionospheric plasma structures across ranges of several thousand kilometers (km). As a byproduct of this technique, the transmitted radar signals frequently reflect from the Earth's surface and can be observed as ground backscatter echoes. The monthly files in this dataset contain maps of daily ground backscatter observations from the Iceland East (ICE) SuperDARN HF radar binned onto an equal-area 24 km grid. The ICE radar is located in Þykkvibær, Iceland (63.77°N (North), 20.54°W (West)) and is operated by Dartmouth College (Principal Investigator: Simon G. Shepherd, simon.g.shepherd@dartmouth.edu) with funding support from the National Science Foundation.more » « less
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The Super Dual Auroral Radar Network (SuperDARN) is an international network of ground-based, space weather radars which have operated continuously in the Arctic and Antarctic regions for more than 30 years. These high-frequency (HF) radars use over-the-horizon (OTH) radio wave propagation to detect ionospheric plasma structures across ranges of several thousand kilometers (km). As a byproduct of this technique, the transmitted radar signals frequently reflect from the Earth's surface and can be observed as ground backscatter echoes. The monthly files in this dataset contain maps of daily ground backscatter observations from the Iceland West (ICW) SuperDARN HF radar binned onto an equal-area 24 km grid. The ICW radar is located in Þykkvibær, Iceland (63.77°N, 20.54°W) and is operated by Dartmouth College (Principal Investigator: Simon G. Shepherd, simon.g.shepherd@dartmouth.edu) with funding support from the National Science Foundation.more » « less
