Numerical considerations in simulating the global magnetosphere

Ridley, A. J.; Gombosi, T. I.; Соколов, И. В.; Tóth, G.; Welling, D. T.

doi:10.5194/angeo-28-1589-2010

Cited by 50 publications

(55 citation statements)

References 101 publications

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“…Further work should investigate the long-term model effects of the starting conditions for TIE-GCM (and physics models in general). Ridley et al (2010) showed the influence of grid choice for global MHD code and it seems that something similar is happening with global ionospheric-thermospheric models.…”

Section: Resultsmentioning

confidence: 84%

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Improved forecasting of thermospheric densities using multi-model ensembles

2016

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Abstract. This paper presents the first known application of multi-model ensembles to the forecasting of the thermosphere. A multi-model ensemble (MME) is a method for combining different, independent models. The main advantage of using an MME is to reduce the effect of model errors and bias, since it is expected that the model errors will, at least partly, cancel. The MME, with its reduced uncertainties, can then be used as the initial conditions in a physics-based thermosphere model for forecasting. This should increase the forecast skill since a reduction in the errors of the initial conditions of a model generally increases model skill. In this paper the Thermosphere-Ionosphere Electrodynamic General Circulation Model (TIE-GCM), the US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter radar Exosphere 2000 (NRLMSISE-00), and Global IonosphereThermosphere Model (GITM) have been used to construct the MME. As well as comparisons between the MMEs and the "standard" runs of the model, the MME densities have been propagated forward in time using the TIE-GCM. It is shown that thermospheric forecasts of up to 6 h, using the MME, have a reduction in the root mean square error of greater than 60 %. The paper also highlights differences in model performance between times of solar minimum and maximum.

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Section: Resultsmentioning

confidence: 84%

“…Whilst necessary, this reduction introduces inaccuracies. Ridley et al (2010) showed that solving the magnetohydrodynamics (MHD) equations numerically rather than analytically can cause significant differences in global MHD code. The same piece of code can give very different results by simply altering the numerical settings.…”

Section: Multi-model Ensemblesmentioning

confidence: 99%

Improved forecasting of thermospheric densities using multi-model ensembles

2016

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“…It should be noted that a global MHD simulation does not necessarily converge towards the same solution even if resolution is improved (Ridley et al, 2010). In fact, if resolution is improved, numerical diffusion decreases, which means that the role of MHD physics as an error source grows.…”

Section: Discussionmentioning

confidence: 99%

The impact on global magnetohydrodynamic simulations from varying initialisation methods: results from GUMICS-4

et al. 2017

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Abstract. We investigate the effects of different initialisation methods of the GUMICS-4 global magnetohydrodynamic (MHD) simulation to the dynamics in different parts of the Earth's magnetosphere and hence compare five 12 h simulation runs that were initiated by 3 h of synthetic data and followed by 9 h of solar wind measurements using the OMNI data as input. As a reference, we use a simulation run that includes nearly 60 h of OMNI data as input prior to the 9 h interval examined with different initialisations. The selected interval is a high-speed stream event during a 10-day interval (12-22 June 2007). The synthetic initialisations include stepwise, linear and sinusoidal functions of the interplanetary magnetic field with constant density and velocity values. The results show that the solutions converge within 1 h to give a good agreement in both the bow shock and the magnetopause position. However, the different initialisation methods lead to local differences which should be taken into consideration when comparing model results to satellite measurements.

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“…The most popular solution so far has been to implement the magnetohydrodynamic (MHD) equations in a global computer simulation. The level of numerical accuracy has been discussed mainly in terms of the order of the solution (see the review by Ridley et al, 2010), while the question remains as to whether the MHD model itself is rich enough to be used as a basic tool for interpreting the system. MHD has proven to give a good description on large scales and where plasma can be described with one temperature (e.g.…”

Section: Introductionmentioning

confidence: 99%