Development of a High‐Latitude Convection Model by Application of Machine Learning to SuperDARN Observations
Abstract A new model of northern hemisphere high‐latitude convection derived using machine learning (ML) is presented. The ML algorithm random forests regression was applied to a database of velocities derived from the Super Dual Auroral Radar Network (SuperDARN) observations processed with the pote...
Saved in:
| Main Authors: | W. A. Bristow, C. A. Topliff, M. B. Cohen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Space Weather |
| Online Access: | https://doi.org/10.1029/2021SW002920 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Model of High Latitude Ionospheric Convection Derived From SuperDARN EOF Model Data
by: M. M. Lam, et al.
Published: (2023-07-01) -
On the Use of SuperDARN Ground Backscatter Measurements for Ionospheric Propagation Model Validation
by: Joshua J. Ruck, et al.
Published: (2024-09-01) -
The Fast Borealis Ionosphere: High Time‐Resolution Mapping of Polar Ionospheric Flows With SuperDARN
by: D. D. Billett, et al.
Published: (2025-06-01) -
The obstructed hernia dilemma: lichtenstein or darn? a comprehensive comparison lichtenstein vs darn repair
by: Shahzeena Kaleem, et al.
Published: (2025-05-01) -
Jovian Injections Observed at High Latitude
by: D. K. Haggerty, et al.
Published: (2019-08-01)