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- Gábor Tóth, Igor V Sokolov, Tamas I Gombosi, David R Chesney, C Robert Clauer, Darren L De Zeeuw +14 others
- 2005

[1] The Space Weather Modeling Framework (SWMF) provides a high-performance flexible framework for physics-based space weather simulations, as well as for various space physics applications. The SWMF integrates numerical models of the Solar Corona, Upper Atmosphere into a high-performance coupled model. The components can be represented with alternative… (More)

- G Toth, O Volberg, Aaron J Ridley, Tamas I Gombosi, Darren Dezeeuw, Kenneth C Hansen +5 others
- 2004

The Space Weather Modeling Framework (SWMF) has been developed to provide NASA and the modeling community with a high-performance computational tool with " plug-and-play " capabilities to model the physics from the surface of the Sun to the upper atmosphere of the Earth. Its recently released working prototype includes five components for the following… (More)

— To construct a model for ionospheric dynamics, a two step identification technique based on subspace algorithms is used. In the first step a Hammerstein model is identified using subspace algorithms and a basis function expansion for the input nonlinearities. In the second step the Wiener nonlinearity is identified as a standard least squares procedure.… (More)

- C Robert Clauer, Tamas I Gombosi, Darren L De Zeeuw, Aaron J Ridley, Kenneth G Powell, Bram Van Leer +3 others
- 2000

—Taking advantage of the advent of massively parallel computers, sophisticated solution-adaptive techniques, and recent fundamental advances in basic numerical methods we have developed a high performance, adaptive-scale MHD code capable of resolving many of the critical processes in the Sun–Earth system which range over more than nine orders of magnitude.… (More)

Mathematical models of physical phenomena are of critical importance in virtually all applications of science and technology. This paper addresses the problem of how to use data to improve the fidelity of a given model. We approach this problem using retrospective cost optimization, which uses data to recursively update an unknown subsystem interconnected… (More)

- Anthony M D 'amato, Ali, John C Springmann, James W Cutler, Aaron J Ridley, Dennis S Bernstein
- 2011

We develop a method for obtaining state estimates for a possibly nonminimum-phase system in the presence of an unknown harmonic input. We construct a state estimator based on the system model, and then introduce an estimator input provided by an adap-tive feedback model whose goal is to drive the estimated output to the measured output despite the presence… (More)

We consider a data assimilation technique for coupled iono-spheric and thermospheric dynamics. The Global Ionosphere-Thermo-sphere Model (GITM) is used to simulate the ionospheric and thermo-spheric dynamics, and evaluate the performance of the data assimilation scheme that estimates the ion densities and flow speeds. This estimation technique is based on… (More)

T he magnetosphere is the region of space dominated by the magnetic field of the Earth. The size of the magnetosphere and much of its dynamics are affected by the Sun's atmosphere, which flows supersonically away from the Sun past the Earth and the other planets in the form of solar wind. The Sun's magnetic field, which is commonly referred to as the… (More)

Mathematical models of physical phenomena are of critical importance in virtually all applications of science and technology. This paper addresses the problem of how to use data to improve the fidelity of a given model. We approach this problem using retrospective cost optimization, a novel technique that uses data to recursively update an unknown subsystem… (More)