scholarly journals Perturbed Input Ensemble Modeling With the Space Weather Modeling Framework

Space Weather ◽  
2018 ◽  
Vol 16 (9) ◽  
pp. 1330-1347 ◽  
Author(s):  
S. K. Morley ◽  
D. T. Welling ◽  
J. R. Woodroffe
Keyword(s):  
Space Weather ◽  
Ensemble Modeling ◽  
Modeling Framework ◽  
Weather Modeling

scholarly journals Integration of RAM-SCB into the Space Weather Modeling Framework

2018 ◽  
Vol 177 ◽  
pp. 160-168 ◽  
Author(s):  
Daniel T. Welling ◽  
Gabor Toth ◽  
Vania K. Jordanova ◽  
Yiqun Yu
Keyword(s):  
Space Weather ◽  
Modeling Framework ◽  
Weather Modeling

scholarly journals Halloween Storm Simulations with the Space Weather Modeling Framework

2006 ◽  
Author(s):  
Tamas Gombosi ◽  
Gabor Toth ◽  
Igor Sokolov ◽  
Ward Manchester ◽  
Aaron Ridley ◽  
...  
Keyword(s):  
Space Weather ◽  
Modeling Framework ◽  
Weather Modeling

scholarly journals The Space Weather Modeling Framework Goes Open Access

Eos ◽  
2021 ◽  
Vol 102 ◽  
Author(s):  
Tuija Pulkkinen ◽  
Tamas Gombosi ◽  
Aaron Ridley ◽  
Gabor Toth ◽  
Shasha Zou
Keyword(s):  
Open Access ◽  
Space Weather ◽  
Computational Models ◽  
Power Grid ◽  
Magnetic Storms ◽  
Modeling Framework ◽  
Weather Modeling

A versatile suite of computational models, already used to forecast magnetic storms and potential power grid and telecommunications disruptions, is preparing to welcome a larger group of users.

SOLSTICE: Space Weather Modeling Meets Machine Learning

2020 ◽  
Author(s):  
Tamas Gombosi ◽  
Keyword(s):  
Machine Learning ◽  
Space Weather ◽  
High Performance ◽  
Numerical Models ◽  
Machine Learning Techniques ◽  
Grand Challenge ◽  
Science Data ◽  
Modeling Framework ◽  
Weather Modeling ◽  
Solar Storms

<p>The last decade has truly witnessed the rise of the machine age. The enormous expansion of technology that can generate and manipulate massive amounts of information has transformed all aspects of society. Missions such as SDO and MMS, and numerical models such as the Space Weather Modeling Framework (SWMF) are now routinely generating terabytes of science data, far beyond what can be analyzed directly by humans. Fortunately, concurrent with this explosion in information has come the development of powerful capabilities, such as machine learning (ML) and artificial intelligence (AI), that can retrieve revolutionary new understanding and utility from the massive data sets.<span> </span></p><p><span>SOLSTICE (Solar Storms and Terrestrial Impacts Center) is a recently selected NASA/NSF DRIVE Center. It</span> will serve as the vanguard for developing and applying ML methods, which will then raise the capabilities of the entire community. We will combine next generation ML technology with our world-leading numerical models and the exquisite data from the space missions to make breakthrough advances in Heliophysics understanding and space weather capabilities, and then transition our technology to the CCMC for the benefit of all.</p><p>We use ML to attack Grand Challenge Problems that cover the major aspects of space weather science: (i) use interpretable deep learning models, archived solar observations and high-performance physics-based simulations to identify the onset mechanism of solar flares and coronal mass ejections; and (ii) use high-cadence observations and physics-based feature learning to predict solar storms many hours before eruption, training time-to-event models to predict event times and flare magnitudes using innovative machine learning techniques.</p>

Effect of selecting different simulation configurations on the prediction performance of the Space Weather Modeling Framework regarding ground magnetic perturbations

2020 ◽  
Author(s):  
Norah Kaggwa Kwagala ◽  
Michael Hesse ◽  
Therese M. Jorgensen ◽  
Paul Tenfjord ◽  
Cecilia Norgren ◽  
...  
Keyword(s):  
Space Weather ◽  
Prediction Performance ◽  
Mhd Equations ◽  
Polar Cap ◽  
Modeling Framework ◽  
Inner Magnetosphere ◽  
Integration Schemes ◽  
Magnetic Perturbations ◽  
Weather Modeling ◽  
Ground Magnetic

<p><span>This study investigates the effect of selecting different simulation configurations of the Space Weather Modeling Framework (SWMF) on the predictions of ground magnetic perturbations. A historic geomagnetic storm, the St. Patrick Storm 2015, is simulated with several different model configurations. The objective is to investigate how the different configurations affect the prediction performance regarding ground magnetic perturbations. For each simulation, the modeled ground magnetic perturbations are compared to the measured perturbations from several ground magnetometer stations located at sub-auroral, auroral and polar cap latitudes. Among the magnetometer stations are the Norwegian and Greenland magnetometer chains. The comparison is based on metrics for both <em>ΔB</em> </span><span>and <em>dB/dt</em></span><span>. The SWMF configurations investigated include variations in grid resolution and integration schemes for the MHD equations, and different settings for the inner magnetosphere, the ionosphere electrodynamics, and the magnetosphere-ionosphere coupling. </span></p>

scholarly journals Validation of the Space Weather Modeling Framework using observations from CHAMP and DMSP

Space Weather ◽  
2008 ◽  
Vol 6 (3) ◽  
pp. n/a-n/a ◽  
Author(s):  
H. Wang ◽  
A. J. Ridley ◽  
H. Lühr
Keyword(s):  
Space Weather ◽  
Modeling Framework ◽  
Weather Modeling

scholarly journals The August 24, 2002 coronal mass ejection: when a western limb event connects to earth

2008 ◽  
Vol 4 (S257) ◽  
pp. 391-398 ◽  
Author(s):  
Noé Lugaz ◽  
Ilia I. Roussev ◽  
Igor V. Sokolov
Keyword(s):  
Coronal Mass Ejection ◽  
Space Weather ◽  
Three Dimensional ◽  
Active Regions ◽  
Modeling Framework ◽  
Initiation Mechanism ◽  
Weather Modeling ◽  
Field Lines ◽  
Mass Ejection ◽  
Western Limb

AbstractWe discuss how some coronal mass ejections (CMEs) originating from the western limb of the Sun are associated with space weather effects such as solar energetic particles (SEPs), shocks or geo-effective ejecta at Earth. We focus on the August 24, 2002 coronal mass ejection, a fast (~2000 km s−1) eruption originating from W81. Using a three-dimensional magneto-hydrodynamic simulation of this ejection with the Space Weather Modeling Framework (SWMF), we show how a realistic initiation mechanism enables us to study the deflection of the CME in the corona and the heliosphere. Reconnection of the erupting magnetic field with that of neighboring streamers and active regions modify the solar connectivity of the field lines connecting to Earth and can also partly explain the deflection of the eruption during the first tens of minutes. Comparing the results at 1 AU of our simulation with observations by the ACE spacecraft, we find that the simulated shock does not reach Earth, but has a maximum angular span of about 120°, and reaches 35° West of Earth in 58 hours. We find no significant deflection of the CME and its associated shock wave in the heliosphere, and we discuss the consequences for the shock angular span.

scholarly journals Space Weather Modeling Framework: A new tool for the space science community

2005 ◽  
Vol 110 (A12) ◽  
Author(s):  
Gábor Tóth ◽  
Igor V. Sokolov ◽  
Tamas I. Gombosi ◽  
David R. Chesney ◽  
C. Robert Clauer ◽  
...  
Keyword(s):  
Space Weather ◽  
Space Science ◽  
Modeling Framework ◽  
Science Community ◽  
Weather Modeling
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