The ground‐based magnetometer index of Dst is a commonly used measure of near‐Earth current systems, in particular the storm time inner magnetospheric current systems. The ability of a large‐scale, physics‐based model to reproduce, or even predict, this index is therefore a tangible measure of the overall validity of the code for space weather research and space weather operational usage. Experimental real‐time simulations of the Space Weather Modeling Framework (SWMF) are conducted at the Community Coordinated Modeling Center (CCMC). Presently, two configurations of the SWMF are running in real time at CCMC, both focusing on the geospace modules, using the Block Adaptive Tree Solar wind‐type Roe Upwind Solver magnetohydrodynamic model, the...
The Pulkkinen et al. (2013) study evaluated the ability of five different geospace models to predict...
Space weather represents a severe threat to ground-based infrastructure, satellites and communicatio...
Extreme space weather events are rare, and quantifying their likelihood is challenging, often relyin...
We simulated the entire month of January 2005 using the Space Weather Modeling Framework (SWMF) with...
As the DoD\u27s use of space and space assets increases, so does its need for timely and accurate pr...
In this paper, an operational Dst index prediction model is developed by combining empirical and Art...
We study the performance of four magnetohydrodynamic models (BATS-R-US, GUMICS, LFM, OpenGGCM) in th...
In this study we investigate the performance of the University of Michigan’s Space Weather Modeling ...
We present a new model for the probability that the Disturbance storm time (Dst) index exceeds -100 ...
[1] We evaluate the performance of recent empirical magnetic field models (Tsyganenko, 1996, 2002a, ...
Geomagnetic indices are convenient quantities that distill the complicated physics of some region or...
[1] We compare global magnetohydrodynamic (MHD) simulation results with an empirical model and obser...
As many systems and equipment are sensitive to magnetic disturbances, it is important to understand ...
Space weather represents a severe threat to ground-based infrastructure, satellites and communicatio...
Space weather events can have damaging effects on ground-based infrastructure. Geomagnetically induc...
The Pulkkinen et al. (2013) study evaluated the ability of five different geospace models to predict...
Space weather represents a severe threat to ground-based infrastructure, satellites and communicatio...
Extreme space weather events are rare, and quantifying their likelihood is challenging, often relyin...
We simulated the entire month of January 2005 using the Space Weather Modeling Framework (SWMF) with...
As the DoD\u27s use of space and space assets increases, so does its need for timely and accurate pr...
In this paper, an operational Dst index prediction model is developed by combining empirical and Art...
We study the performance of four magnetohydrodynamic models (BATS-R-US, GUMICS, LFM, OpenGGCM) in th...
In this study we investigate the performance of the University of Michigan’s Space Weather Modeling ...
We present a new model for the probability that the Disturbance storm time (Dst) index exceeds -100 ...
[1] We evaluate the performance of recent empirical magnetic field models (Tsyganenko, 1996, 2002a, ...
Geomagnetic indices are convenient quantities that distill the complicated physics of some region or...
[1] We compare global magnetohydrodynamic (MHD) simulation results with an empirical model and obser...
As many systems and equipment are sensitive to magnetic disturbances, it is important to understand ...
Space weather represents a severe threat to ground-based infrastructure, satellites and communicatio...
Space weather events can have damaging effects on ground-based infrastructure. Geomagnetically induc...
The Pulkkinen et al. (2013) study evaluated the ability of five different geospace models to predict...
Space weather represents a severe threat to ground-based infrastructure, satellites and communicatio...
Extreme space weather events are rare, and quantifying their likelihood is challenging, often relyin...