Space weather describes the interactions in the Sun-Earth system that affects human technologies and health, including damages of satellites, loss of communication, degraded accuracy of global positioning systems, safety of astronauts and air plane pilots and passengers flying along polar routes. Modeling and eventually predicting space weather is therefore a practically important challenge.

The Center for Space Environment Modeling (CSEM) at the University of Michigan has been at the fore-front of physics-based space weather modeling. Our group has developed the Space Weather Modeling Framework (SWMF) that integrates independently developed models into a high performance simulation tool. The SWMF models physics domains spanning from the solar corona and heliosphere to the magnetosphere, ionosphere and thermosphere of the Earth. The SWMF can perform a realistic Sun-to-thermosphere simulation faster than real time on today's supercomputers.

I will describe the SWMF and some of the numerical techniques that enable achieving the required performance.

Solar energetic particle (SEP) events are one of the most severe hazards of the solar induced space weather phenomena. SEP events eventually occur in nature and can lead to large radiation doses, either in short time intervals or by accumulation in extended periods. The radiation risks that these events pose to spacecraft operations and manned missions have extensively been reviewed elsewhere. The most significant sources of SEP fluxes in the interplanetary medium are solar flares and shock waves driven by coronal mass ejections (CMEs).

Critical to the ability to design space missions is our capacity for predicting SEP fluxes and fluences. The Solar Particle Engineering code (SOLPENCO) is based on the combined shock-and-particle developed by Lario et al. (1998). SOLPENCO allows the user to obtain flux and fluence predictions of gradual SEP events originating from far western to far eastern locations, as seen at two heliocentric radial distances: 1 and 0.4 AU. The considered proton energy channels extend up to 90 MeV, to accommodate the range of energies causing space weather effects. SOLPENCO is a first step toward a fully and reliable operational tool for the prediction of SEP event fluxes and fluences, but a large ling effort is needed in order to fix the drawbacks of the shock-and-particle and those of SOLPENCO itself. I present the description of how we have built SOLPENCO, that is, I show the transition from the physics-based to the tool. And I discuss the limitations of SOLPENCO, as well as the steps we are following for its improvement.

Reference:
Lario, D., Sanahuja, B. and Heras, A.M., Astrophysical J., 509, 415-435 (1998).

A three dimensional physical dynamic model of the plasmasphere has been developed at the Belgian Institute for Space Aeronomy. The plasmaspheric model is based on the kinetic approach and the parameters of the model are constrained to fit empirical density profiles. The position of the plasmapause is determined by the interchange instability mechanism and depends on the level of geomagnetic activity. The deformation of the plasmasphere during quiet and disturbed geomagnetic periods is compared with observations of IMAGE and CLUSTER.

This physical model is analytical, and consequently easy to implement: it does not require large computer resources and is fairly portable. Furthermore, it incorporates major physical features that determine the density distributions in flux tubes at high altitudes.

The plasmapause position prediction is useful for the scientific community because its location determines the influence of wave-particle interaction processes on radiation belts formation. Moreover, even if plasmaspheric densities are considerably less than those of the ionosphere, the large extent of the plasmasphere has implications for the Earth's ionosphere and can affect radio transmissions and GPS signals.

SWIF (Solar Wind driven autoregression model for Ionospheric short term Forecast) is an empirical model for the short term prediction of the critical ionospheric parameter foF2 at middle latitudes. It issues predictions based on an autoregression forecasting algorithm, namely TSAR, analyzing in the same time with the SWIF alert detection algorithm continuously streaming interplanetary magnetic field (IMF) data from ACE satellite to estimate storm triggering conditions in the solar wind. Upon the determination of storm alert conditions, an empirical storm time ionospheric model, namely STIM, is activated to predict forthcoming ionospheric disturbances. SWIF’s performance has been evaluated in comparison to both actual observations and predictions of well known ionospheric forecasting models under all possible ionospheric conditions and considerable improvements in the prediction accuracy have been demonstrated. Therefore, SWIF can be considered as a new ionospheric forecasting method that provides significant advances towards the successful ionospheric forecasts. Moreover, the operational implementation of SWIF, which is based on the availability of IMF observations from L1 point in real-time, can efficiently support the development of ionospheric forecasting space weather services. In this paper, SWIF’s operational implementation in the European Digital Upper Atmosphere Server (DIAS) (http://dias.space.noa.gr) is particularly discussed, aiming at the substantial upgrade of DIAS ionospheric forecasting services that include issuing of alerts and warnings for upcoming ionospheric disturbances as well as ionospheric predictions for all DIAS locations and ionospheric forecasting maps for the European region.

Operational monitoring and prediction of space weather events would be a key part of any future European programme for Space Situational Awareness. A significant component of space weather service provision is the analysis and forecasting of the state of the ionosphere, which is of interest both to academics and to a variety of users, in particular those whose activities depend upon radio telecommunications or Global Navigation Satellite Systems (GNSS). Although meteorological services, such as the Met Office, produce and disseminate analyses of the lower and middle atmosphere, there is no equivalent provision within Europe for global analyses of the ionosphere and thermosphere.

A recent development in the area of space weather prediction has been the growing realisation that operational meteorological services could potentially plug the gap within Europe for ionospheric analyses. This is in part because numerical modelling of atmospheric physics in the thermosphere, ionosphere and plasmasphere has reached a degree of sophistication where it is plausible to consider the development of global data assimilation systems which combine forecast models with observations to produce analyses of the ionosphere. The emergence of operational systems to produce a routine analysis state of the ionosphere would imply a well-developed infrastructure for:

The Center for Integrated Space Weather Modeling (CISM) is a US National Science Foundation (NSF) funded project which consists of research groups at eight universities and several government and private research organizations. The goal is to construct a comprehensive numerical model of the space environment by focusing on coupled modeling of the solar atmosphere, solar wind, the magnetosphere, ionosphere and thermosphere.

An important aspect of the project is the coupling of the Lyon-Fedder-Mobarry (LFM) model of the magnetosphere with the Thermosphere Ionosphere Electrodynamic General Circulation Model (TIEGCM) to create the Coupled Magnetosphere Ionosphere Thermosphere model (CMIT). I will describe the CMIT model and then discuss the transitioning of the model from it's academic research basis to a real-time space weather forecast model running at the NOAA, National Weather Service, Space Weather Prediction Center (SWPC). Results will be shown for CMIT simulations driven by measurements of the solar wind from the ACE spacecraft to produce estimates of regional ground magnetic disturbance and ionospheric Total Electron Content (TEC).

Statistical space radiation models based on averages of all measured values include variances that result from storm-time transients. Such models fade away the characteristics of physical processes that drive the dynamic of particle flux variations. We intend to break with classical model approaches and go beyond the existing static radiation models (AP8, AE8,...) by introducing dynamic features based on observations of transient flux events. This approach is expected to facilitate the investigation of the physical processes involved in the flux variations in the magnetosphere.

Our dynamic model is based on the assumption that the particle fluxes at a given position in space are composed of a steady state background and a magnetic activity-dependent value that is a function of (i) the elapsed time after the latest geomagnetic storm (GS), (ii) the intensity of the latest GS, (iii) the occurrence probability for a new GS regarding its type and the phase within the solar cycle, (iv) the flux level prior to the latest GS and (v) the local flux decay time.

To obtain all the parameters that are involved in the model four main studies are underway:

During magnetic storms solar wind generated magnetospheric currents constitute a significant source to magnetic field perturbations near the Earth surface. Perturbations which in turn influence radiation levels at low Earth orbit. Most prominent and also most well described is the effect of the magnetospheric ring current, but also magnetopause currents, partial ring current and tail currents play a role. Least well describe is probably the long-distance effect of the high-latitude field-aligned currents.

Global MHD modelling constitutes a physics based approach to estimate magnetopause- and tail-currents, and is a particular useful tool for investigating how these currents vary with the solar wind parameters. Modelling of the long-distance effect of FACs, on the other hand, requires accurate mapping of the high latitude FAC patterns. We use FAC patterns estimated from ground magnetic stations and low altitude orbiting satellites as well as a model run of the OpenGGCM performed at the Community Coordinated Modelling Center (CCMC) to estimate the 3D-distribution of magnetopause and tail currents. From these models we estimate the associated low- and mid-latitude magnetic disturbances using Biot-Savart integration. Focus is on the analysis of a typical storm from quiet times through ssc, storm main phase to the recovery phase.