More Like this

1. A Probabilistic Assessment of the Next Geomagnetic Reversal: NEXT GEOMAGNETIC REVERSAL

   https://doi.org/10.1002/2018GL077061  

   Buffett, Bruce; Davis, William (February 2018, Geophysical Research Letters)
2. Thermosphere modeling capabilities assessment: geomagnetic storms

   https://doi.org/10.1051/swsc/2021002  

   Bruinsma, Sean; Boniface, Claude; Sutton, Eric K.; Fedrizzi, Mariangel (January 2021, Journal of Space Weather and Space Climate)

   null (Ed.)

   The specification and prediction of density fluctuations in the thermosphere, especially during geomagnetic storms, is a key challenge for space weather observations and modeling. It is of great operational importance for tracking objects orbiting in near-Earth space. For low-Earth orbit, variations in neutral density represent the most important uncertainty for propagation and prediction of satellite orbits. An international conference in 2018 conducted under the auspices of the NASA Community Coordinated Modeling Center (CCMC) included a workshop on neutral density modeling, using both empirical and numerical methods, and resulted in the organization of an initial effort of model comparison and evaluation. Here, we present an updated metric for model assessment under geomagnetic storm conditions by dividing a storm in four phases with respect to the time of minimum Dst and then calculating the mean density ratios and standard deviations and correlations. Comparisons between three empirical (NRLMSISE-00, JB2008 and DTM2013) and two first-principles models (TIE-GCM and CTIPe) and neutral density data sets that include measurements by the CHAMP, GRACE, and GOCE satellites for 13 storms are presented. The models all show reduced performance during storms, notably much increased standard deviations, but DTM2013, JB2008 and CTIPe did not on average reveal a significant bias in the four phases of our metric. DTM2013 and TIE-GCM driven with the Weimer model achieved the best results taking the entire storm event into account, while NRLMSISE-00 systematically and significantly underestimates the storm densities. Numerical models are still catching up to empirical methods on a statistical basis, but as their drivers become more accurate and they become available at higher resolutions, they will surpass them in the foreseeable future. 

   more » « less
3. Modeling geomagnetic induction in submarine cables

   https://doi.org/10.3389/fphy.2022.1022475  

   Chakraborty, Shibaji; Boteler, David H.; Shi, Xueling; Murphy, Benjamin S.; Hartinger, Michael D.; Wang, Xuan; Lucas, Greg; Baker, Joseph B. (October 2022, Frontiers in Physics)

   Submarine cables have become a vital component of modern infrastructure, but past submarine cable natural hazard studies have mostly focused on potential cable damage from landslides and tsunamis. A handful of studies examine the possibility of space weather effects in submarine cables. The main purpose of this study is to develop a computational model, using Python , of geomagnetic induction on submarine cables. The model is used to estimate the induced voltage in the submarine cables in response to geomagnetic disturbances. It also utilizes newly acquired knowledge from magnetotelluric studies and associated investigations of geomagnetically induced currents in power systems. We describe the Python-based software, its working principle, inputs/outputs based on synthetic geomagnetic field data, and compare its operational capabilities against analytical solutions. We present the results for different model inputs, and find: 1) the seawater layer acts as a shield in the induction process: the greater the ocean depth, the smaller the seafloor geoelectric field; and 2) the model is sensitive to the Ocean-Earth layered conductivity structure. 

   more » « less
4. A grand spectrum of the geomagnetic field

   https://doi.org/10.1016/j.pepi.2023.107090  

   Constable, Catherine; Constable, Steven (November 2023, Physics of the Earth and Planetary Interiors)
5. Statistics of geomagnetic storms: Global simulations perspective

   https://doi.org/10.3389/fspas.2022.972150  

   Pulkkinen, Tuija I.; Brenner, Austin; Al Shidi, Qusai; Toth, Gabor (September 2022, Frontiers in Astronomy and Space Sciences)

   We present results of 131 geomagnetic storm simulations using the University of Michigan Space Weather Modeling Framework Geospace configuration. We compare the geomagnetic indices derived from the simulation with those observed, and use 2D cuts in the noon-midnight planes to compare the magnetopause locations with empirical models. We identify the location of the current sheet center and look at the plasma parameters to deduce tail dynamics. We show that the simulation produces geomagnetic index distributions similar to those observed, and that their relationship to the solar wind driver is similar to that observed. While the magnitudes of the Dst and polar cap potentials are close to those observed, the simulated AL index is consistently underestimated. Analysis of the magnetopause position reveals that the subsolar position agrees well with an empirical model, but that the tail flaring in the simulation is much smaller than that in the empirical model. The magnetotail and ring currents are closely correlated with the Dst index, and reveal a strong contribution of the tail current beyond 8 R E to the Dst index during the storm main phase. 

   more » « less