A. Pulkkinen

Generation of 100‐year geomagnetically induced current scenarios

A series of 100-year extreme geoelectric field and geomagnetically induced current (GIC) scenarios are explored by taking into account the key geophysical factors associated with the geomagnetic induction process. More specifically, we derive explicit geoelectric field temporal profiles as a function of ground conductivity structures and geomagnetic latitudes. We also demonstrate how the extreme geoelectric field scenarios can be mapped into GIC. Generated statistics indicate 20 V/km and 5 V/km 100-year maximum 10-s geoelectric field amplitudes at high-latitude locations with poorly conducting and well-conducting ground structures, respectively. We show that there is an indication that geoelectric field magnitudes may experience a dramatic drop across a boundary at about 40°–60° of geomagnetic latitude. We identify this as a threshold at about 50° of geomagnetic latitude. The sub-threshold geoelectric field magnitudes are about an order of magnitude smaller than those at super-threshold geomagnetic latitudes. Further analyses are required to confirm the existence and location of the possible latitude threshold. The computed extreme GIC scenarios can be used in further engineering analyses that are needed to quantify the geomagnetic storm impact on conductor systems such as high-voltage power transmission systems. To facilitate further work on the topic, the digital data for generated geoelectric field scenarios are made publicly available.

Geospace Environment Modeling 2008–2009 Challenge: Ground magnetic field perturbations

helps the users of the modeling products to better understand the capabilities of the models and to choose the approach that best suits their specific needs. Further, metrics!based analyses are important for addressing the differences between various modeling approaches and for measuring and guiding the progress in the field. In this paper, the metrics!based results of the ground magnetic field perturbation part of the Geospace Environment Modeling 2008‐2009 Challenge are reported. Predictions made by 14 different models, including an ensemble model, are compared to geomagnetic observatory recordings from 12 different northern hemispheric locations. Five different metrics are used to quantify the model performances for four storm events. It is shown that the ranking of the models is strongly dependent on the type of metric used to evaluate the model performance. None of the models rank near or at the top systematically for all used metrics. Consequently, one cannot pick the absolute“winner”: the choice for the best model depends on the characteristics of the signal one is interested in. Model performances vary also from event to event. This is particularly clear for root!mean!square difference and utility metric!based analyses. Further, analyses indicate that for some of the models, increasing the global magnetohydrodynamic model spatial resolution and the inclusion of the ring current dynamics improve the models’capability to generate more realistic ground magnetic field fluctuations.

Evaluating predictions of ICME arrival at Earth and Mars

[1]xa0We present a study of interplanetary coronal mass ejection (ICME) propagation to Earth and Mars. Because of the significant space weather hazard posed by ICMEs, understanding and predicting their arrival and impact at Mars is important for current and future robotic and manned missions to the planet. We compare running ENLILv2.6 with coronal mass ejection (CME) input parameters from both a manual and an automated method. We analyze shock events identified at Mars in Mars Global Surveyor data in 2001 and 2003, when Earth and Mars were separated by <80° in heliocentric longitude. The shocks identified at Mars were also identified at Earth, and the majority of the shock sources were identified through the Solar and Heliospheric Observatory–Large Angle and Spectrometric Coronagraph catalogue. We find that arrival times predicted by the two methods at both planets are statistically similar, dynamic pressures predicted when using the automated method are better, and the automated method tends to underestimate both CME width and speed. Using the location of the related flare as the CME direction did not improve results. In addition, changing the CME speed toward the plane-of-sky speed at 20 RS improves the match to observations, mainly because the speed found by the automated method is underestimated. The time lapse between the shock arrival at Earth and Mars, for the events studied here, is shorter than expected from simulations, and the presence of high speed streams can enable an ICME to arrive almost simultaneously at Earth and Mars. This work will be applied to improve the input parameter methods for ENLIL.

Modeling of coronal mass ejections that caused particularly large geomagnetic storms using ENLIL heliosphere cone model

[1]xa0In our previous paper we reported the results of modeling of 14 selected well-observed strong halo coronal mass ejection (CME) events using the WSA-ENLIL cone model combination. Cone model input parameters were obtained from white light coronagraph images of the CME events using the analytical method developed by Xie et al. (2004). This work verified that coronagraph input gives reasonably good results for the CME arrival time prediction. In contrast to Taktakishvili et al. (2009), where we started the analysis by looking for clear CME signatures in the data and then proceeded to model the interplanetary consequences at 1 AU, in the present paper we start by generating a list of observed geomagnetic storm events and then work our way back to remote solar observations and carry out the corresponding CME modeling. The approach used in this study is addressing space weather forecasting and operational needs. We analyzed 36 particularly strong geomagnetic storms, then tried to associate them with particular CMEs using SOHO/LASCO catalogue, and finally modeled these CMEs using WSA-ENLIL cone model. Recently, Pulkkinen et al. (2010) developed a novel method for automatic determination of cone model parameters. We employed both analytical and automatic methods to determine cone model input parameters. We examined the CME arrival times and magnitude of impact at 1 AU for both techniques. The results of the simulations are compared with the ACE satellite observations. This comparison demonstrated that WSA-ENLIL model combination with coronagraph input gives reasonably good results for the CME arrival times for this set of “geoeffective” CME events as well.

Tracking the Momentum Flux of a CME and Quantifying Its Influence on Geomagnetically Induced Currents at Earth

[1]xa0We investigate a coronal mass ejection (CME) propagating toward Earth on 29 March 2011. This event is specifically chosen for its predominately northward directed magnetic field, so that the influence from the momentum flux onto Earth can be isolated. We focus our study on understanding how a small Earth-directed segment propagates. Mass images are created from the white-light cameras onboard STEREO which are also converted into mass height-time maps (mass J-maps). The mass tracks on these J-maps correspond to the sheath region between the CME and its associated shock front as detected by in situ measurements at L1. A time series of mass measurements from the STEREO COR-2A instrument is made along the Earth propagation direction. Qualitatively, this mass time series shows a remarkable resemblance to the L1 in situ density series. The in situ measurements are used as inputs into a three-dimensional (3-D) magnetospheric space weather simulation from the Community Coordinated Modeling Center. These simulations display a sudden compression of the magnetosphere from the large momentum flux at the leading edge of the CME, and predictions are made for the time derivative of the magnetic field (dB/dt) on the ground. The predicted dB/dt values were then compared with the observations from specific equatorially located ground stations and showed notable similarity. This study of the momentum of a CME from the Sun down to its influence on magnetic ground stations on Earth is presented as a preliminary proof of concept, such that future attempts may try to use remote sensing to create density and velocity time series as inputs to magnetospheric simulations.

Transforming community access to space science models

Researching and forecasting the ever changing space environment (often referred to as space weather) and its influence on humans and their activities are model-intensive disciplines. This is true because the physical processes involved are complex, but, in contrast to terrestrial weather, the supporting observations are typically sparse. Models play a vital role in establishing a physically meaningful context for interpreting limited observations, testing theory, and producing both nowcasts and forecasts. For example, with accurate forecasting of hazardous space weather conditions, spacecraft operators can place sensitive systems in safe modes, and power utilities can protect critical network components from damage caused by large currents induced in transmission lines by geomagnetic storms.