Bibliography

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Found 13 entries in the Bibliography.

Showing entries from 1 through 13

2022

Height-integrated polar cap conductances during an average substorm

Carter, Jennifer; Milan, Steven; Lester, Mark; Forsyth, Colin; Paxton, Larry; Gjerloev, Jesper; Anderson, Brian;

Published by: Published on:

YEAR: 2022 DOI:

2021

Toward a Next Generation Particle Precipitation Model: Mesoscale Prediction Through Machine Learning (a Case Study and Framework for Progress)

We advance the modeling capability of electron particle precipitation from the magnetosphere to the ionosphere through a new database and use of machine learning (ML) tools to gain utility from those data. We have compiled, curated, analyzed, and made available a new and more capable database of particle precipitation data that includes 51 satellite years of Defense Meteorological Satellite Program (DMSP) observations temporally aligned with solar wind and geomagnetic activity data. The new total electron energy flux particle precipitation nowcast model, a neural network called PrecipNet, takes advantage of increased expressive power afforded by ML approaches to appropriately utilize diverse information from the solar wind and geomagnetic activity and, importantly, their time histories. With a more capable representation of the organizing parameters and the target electron energy flux observations, PrecipNet achieves a \textgreater50\% reduction in errors from a current state-of-the-art model oval variation, assessment, tracking, intensity, and online nowcasting (OVATION Prime), better captures the dynamic changes of the auroral flux, and provides evidence that it can capably reconstruct mesoscale phenomena. We create and apply a new framework for space weather model evaluation that culminates previous guidance from across the solar-terrestrial research community. The research approach and results are representative of the “new frontier” of space weather research at the intersection of traditional and data science-driven discovery and provides a foundation for future efforts.

McGranaghan, Ryan; Ziegler, Jack; Bloch, Téo; Hatch, Spencer; Camporeale, Enrico; Lynch, Kristina; Owens, Mathew; Gjerloev, Jesper; Zhang, Binzheng; Skone, Susan;

Published by: Space Weather Published on:

YEAR: 2021 DOI: 10.1029/2020SW002684

space weather; magnetosphere-ionosphere coupling; data science; evaluation; machine learning; particle precipitation

Determination of Auroral Electrodynamic Parameters From AMPERE Field-Aligned Current Measurements

We calculate high latitude electrodynamic parameters using global maps of field-aligned currents from the Active Magnetosphere and Planetary Response Experiment (AMPERE). The model is based on previous studies that relate field-aligned currents to auroral Pedersen and Hall conductances measured by incoherent scatter radar. The field-aligned currents and conductances are used to solve for the electric potential at high latitudes from which electric fields are computed. The electric fields are then used with the conductances to calculate horizontal ionospheric currents. We validate the results by simulating the SuperMAG magnetic indices for 30 geomagnetically active days. The correlation coefficients between derived and actual magnetic indices were 0.68, 0.76, and 0.84 for the SMU, SML, and SME indices, respectively. We show examples of times when the simulations differ markedly from the measured indices and attribute them to either small-scale, substorm-related current structures or the effects of neutral winds. Overall, the performance of the model demonstrates that with few exceptions, auroral electrodynamic parameters can be accurately deduced from the global field-aligned current distribution provided by AMPERE.

Robinson, R.; Zanetti, Larry; Anderson, Brian; Vines, Sarah; Gjerloev, Jesper;

Published by: Space Weather Published on:

YEAR: 2021 DOI: 10.1029/2020SW002677

space weather; auroral currents; auroral electrodynamics; conductivities; electric fields; field-aligned currents

2020

Height-Integrated Ionospheric Conductances Parameterized By Interplanetary Magnetic Field and Substorm Phase

Carter, JA; Milan, SE; Paxton, LJ; Anderson, BJ; Gjerloev, J;

Published by: Journal of Geophysical Research: Space Physics Published on:

YEAR: 2020 DOI:

2016

Nightside storm-time Birkeland currents: quasi-steady state, onsets, and dual R1/2 sense pairs

Anderson, BJ; Korth, H; Paxton, LJ; Olson, C; Waters, CL; Barnes, RJ; Gjerloev, JW;

Published by: Published on:

YEAR: 2016 DOI:

Nightside storm-time Birkeland currents: quasi-steady state, onsets, and dual R1/2 sense pairs

Korth, Haje; Anderson, Brian; Paxton, Larry; Olson, Cameron; Waters, Colin; Barnes, Robin; Gjerloev, Jesper;

Published by: Published on:

YEAR: 2016 DOI:

2015

Towards a National Space Weather Predictive Capability

Fox, Nicola; Ryschkewitsch, Michael; Merkin, Viacheslav; Stephens, Grant; Gjerloev, Jesper; Barnes, Robin; Anderson, Brian; Paxton, Larry; Ukhorskiy, Aleksandr; Kelly, Michael; , others;

Published by: Published on:

YEAR: 2015 DOI:

2014

Local Geomagnetic Indices and the Prediction of Auroral Power

The aurora has been related to magnetometer observations for centuries, and to geomagnetic indices for decades. As the number of stations and data processing power increases, just how auroral power (AP) relates to geomagnetic observations becomes a more tractable question. This paper compares Polar UVI AP observations during 1997 with a variety of indices. Local time (LT) versions of the SuperMAG auroral electrojet (SME) are introduced and examined, along with the corresponding upper and lower envelopes (SMU and SML). Also, the East\textendashwest component, B_E, is investigated. We also consider whether using any of the local indices is actually better at predicting local AP than a single global index. Each index is separated into 24 LT indices with a sliding 3-h MLT window. The ability to predict AP varies greatly with LT, peaking at 1900 MLT, where about 75\% of the variance (r²) is predicted at 1-min cadence. The aurora is fairly predictable from 1700 MLT \textendash 0400 MLT, roughly the region in which substorms occur. AP is poorly predicted from auroral electrojet indices from 0500 MLT \textendash 1500 MLT, with the minimum at 1000\textendash1300 MLT. In the region of high predictability, the local index which works best is B_E (East\textendashwest), in contrast to long-standing expectations. However using global SME is better than any local index. AP is best predicted by combining global SME with a local index: B_E from 1500\textendash0300 MLT, and either SMU or SML from 0300\textendash1500 MLT. In the region of the diffuse aurora, it is better to use a 30 min average than the cotemporaneous 1-min SME value, while from 1500\textendash0200 MLT the cotemporaneous 1-min SME works best, suggesting a more direct physical relationship with the auroral circuit. These results suggest a significant role for discrete auroral currents closing locally with Pedersen currents.