Bibliography

A Comparative Study of Spectral Auroral Intensity Predictions From Multiple Electron Transport Models

It is important to routinely examine and update models used to predict auroral emissions resulting from precipitating electrons in Earth\textquoterights magnetotail. These models are commonly used to invert spectral auroral ground-based images to infer characteristics about incident electron populations when in situ measurements are unavailable. In this work, we examine and compare auroral emission intensities predicted by three commonly used electron transport models using varying electron population characteristics. We then compare model predictions to same-volume in situ electron measurements and ground-based imaging to qualitatively examine modeling prediction error. Initial comparisons showed differences in predictions by the GLobal airglOW (GLOW) model and the other transport models examined. Chemical reaction rates and radiative rates in GLOW were updated using recent publications, and predictions showed better agreement with the other models and the same-volume data, stressing that these rates are important to consider when modeling auroral processes. Predictions by each model exhibit similar behavior for varying atmospheric constants, energies, and energy fluxes. Same-volume electron data and images are highly correlated with predictions by each model, showing that these models can be used to accurately derive electron characteristics and ionospheric parameters based solely on multispectral optical imaging data.

Grubbs, Guy; Michell, Robert; Samara, Marilia; Hampton, Donald; Hecht, James; Solomon, Stanley; Jahn, Jörg-Micha;

Published by: Journal of Geophysical Research: Space Physics      Published on: 01/2018

YEAR: 2018     DOI: 10.1002/2017JA025026

The K p index and solar wind speed relationship: Insights for improving space weather forecasts

The Kp geomagnetic index forecasts are currently used to predict the aurora, MeV electron fluxes at geosynchronous, spacecraft anomalies and charging events, and times when accurate geological surveys can be performed. Many Kp forecasts rely on the upstream solar wind speed since the speed strongly correlates with the Kp index. However, the distribution of Kp and solar wind speed measurements is quite broad. To understand how common certain combinations of Kp and speed are, we plot the percentage of points in two-dimensional Kp and speed bins using a color scale. Using these color Kp-solar wind speed distributions for compressions, rarefactions, and Interplanetary Coronal Mass Ejections separately, we find that much of the variability in the Kp-solar wind speed distribution is attributable to the dynamic interaction between the fast and slow wind. We compare three different criteria for identifying compressions and rarefactions and find that density criteria provide greater separation between compressions and rarefactions than dynamic pressure or speed-time slope criteria. However, the speed-time slope provides enough separation to be useful given that the solar wind speed has a long autocorrelation time and can be predicted using solar observations (e.g., expansion factor models). To ensure our work can easily be incorporated into forecast models, we provide the Kp-speed distributions files for all three methods of identifying compressions and rarefactions. We describe a method to extend forecast lead times by estimating compression strength with a speed-time profile obtained from solar wind speed predictions based on solar, coronal, and/or heliospheric imaging observations.

Elliott, Heather; Jahn, Jörg-Micha; McComas, David;

Published by: Space Weather      Published on: 06/2013

YEAR: 2013     DOI: 10.1002/swe.20053

Kp; solar wind speed; space weather forecasts

The Kp index and solar wind speed relationship: Insights for improving space weather forecasts

The Kp geomagnetic index forecasts are currently used to predict the aurora, MeV electron fluxes at geosynchronous, spacecraft anomalies and charging events, and times when accurate geological surveys can be performed. Many Kp forecasts rely on the upstream solar wind speed since the speed strongly correlates with the Kp index. However, the distribution of Kp and solar wind speed measurements is quite broad. To understand how common certain combinations of Kp and speed are, we plot the percentage of points in two-dimensional Kp and speed bins using a color scale. Using these color Kp-solar wind speed distributions for compressions, rarefactions, and Interplanetary Coronal Mass Ejections separately, we find that much of the variability in the Kp-solar wind speed distribution is attributable to the dynamic interaction between the fast and slow wind. We compare three different criteria for identifying compressions and rarefactions and find that density criteria provide greater separation between compressions and rarefactions than dynamic pressure or speed-time slope criteria. However, the speed-time slope provides enough separation to be useful given that the solar wind speed has a long autocorrelation time and can be predicted using solar observations (e.g., expansion factor models). To ensure our work can easily be incorporated into forecast models, we provide the Kp-speed distributions files for all three methods of identifying compressions and rarefactions. We describe a method to extend forecast lead times by estimating compression strength with a speed-time profile obtained from solar wind speed predictions based on solar, coronal, and/or heliospheric imaging observations.

Elliott, Heather; Jahn, Jörg-Micha; McComas, David;

Published by: Space Weather      Published on:

YEAR: 2013     DOI: https://doi.org/10.1002/swe.20053

space weather forecasts; Kp; solar wind speed

Seasonal and Latitudinal Variations of the F2-Layer during Magnetic Storms

Park, Yoon-Kyung; Kwak, Young-Sil; Ahn, Byung-Ho;

Published by: Journal of Astronomy and Space Sciences      Published on:

YEAR: 2013     DOI:

Optical communications development for spacecraft applications

Bradley G. Boone, Jonathan R. Bruzzi, Bernard E. Kluga, Wesley P. Millard, Karl B. Fielhauer, Donald D. Duncan, Daniel V. Hahn, Christian W. Drabenstadt, Donald E. Maurer, and

Boone, Bradley; Bruzzi, Jonathan; Kluga, Bernard; Millard, Wesley; Fielhauer, Karl; Duncan, Donald; Hahn, Daniel; Drabenstadt, Christian; Maurer, Donald; Bokulic, Robert;

Published by: Johns Hopkins APL technical digest      Published on:

YEAR: 2004     DOI:

Conductance Effects on Inner Magnetospheric Plasma Morphology: Model Comparisons With IMAGE EUV, MENA, and HENA Data

Liemohn, MW; Ridley, AJ; Kozyra, JU; Gallagher, DL; Henderson, MG; Denton, MH; Jahn, J; Roelof, EC; DeMajistre, R; Mitchell, DG; , others;

Published by:       Published on:

YEAR: 2004     DOI: