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1. A Comparison of FDTD-Predicted Surface Magnetic Fields with SuperMAG, INTERMAGNET, and BATS-R-US and RIM Virtual Magnetometers during a Geomagnetic Storm

   Zhang, Yisong; Simpson, Jamesina J.; Ridley, Aaron; Welling, Dan; Liemohn, Michael (January 2020, Proc. American Geophysical Union Fall Meeting)

   null (Ed.)

   The historical record indicates the possibility of intense coronal mass ejections (CMEs). Energized particles and magnetic fields ejected by coronal mass ejections (CMEs) towards the Earth may disrupt the Earth’s magnetosphere and generate a geomagnetic storm. During a geomagnetic storm, the induced geoelectric field can drive geomagnetically-induced currents (GICs) that flow through ground-based conductors. These GICs have the potential to damage high voltage power transmission systems and cause blackouts. As part of the NSF-funded Comprehensive Hazard Analysis for Resilience to Geomagnetic Extreme Disturbances (CHARGED) project, a solar-wind-to-lithosphere numerical model of the geoelectric field is being developed. The purpose of this new tool is to drive a new generation of GIC forecasting. As a part of that work, Maxwell’s equations, finite-difference time-domain (FDTD) models of the last stage of the Sun-to-Earth propagation path is being coupled to output generated by the Block Adaptive Tree Solarwind Roe-type Upwind Scheme (BATS-R-US) magnetohydrodynamics model and the Ridley Ionosphere Model (RIM) of ionospheric dynamics. Specifically, three-dimensional (3-D) BATS-R-US and RIM-predicted ionospheric currents occurring in the lower ionosphere during and around the time of the March 17, 2015 storm are modeled in 3-D FDTD models of North America. These models start at a depth of 150 km, and they account for ionospheric currents occurring up to an altitude of 115 km. The resolution of the FDTD models is 22 km (East-West) x 11 km (North-South) x 5 km (radially), and they account for 3-D lithosphere conductivities provided by the U.S. Geological Survey. The FDTD-calculated results are compared with surface magnetic fields measured in the region by SuperMAG and INTERMAGNET magnetometers. The FDTD results are also compared with virtual magnetometer data, which calculates the perturbation of the surface magnetic field using output from the BATS-R-US magnetohydrodynamics model. Comparison plots and an analysis of the results will be provided. 

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2. On the Regional Variability of d B /d t and Its Significance to GIC

   https://doi.org/10.1029/2020SW002497  

   Dimmock, A_P; Rosenqvist, L.; Welling, D_T; Viljanen, A.; Honkonen, I.; Boynton, R_J; Yordanova, E. (August 2020, Space Weather)

   Abstract Faraday's law of induction is responsible for setting up a geoelectric field due to the variations in the geomagnetic field caused by ionospheric currents. This drives geomagnetically induced currents (GICs) which flow in large ground‐based technological infrastructure such as high‐voltage power lines. The geoelectric field is often a localized phenomenon exhibiting significant variations over spatial scales of only hundreds of kilometers. This is due to the complex spatiotemporal behavior of electrical currents flowing in the ionosphere and/or large gradients in the ground conductivity due to highly structured local geological properties. Over some regions, and during large storms, both of these effects become significant. In this study, we quantify the regional variability ofdB/dtusing closely placed IMAGE stations in northern Fennoscandia. The dependency between regional variability, solar wind conditions, and geomagnetic indices are also investigated. Finally, we assess the significance of spatial geomagnetic variations to modeling GICs across a transmission line. Key results from this study are as follows: (1) Regional geomagnetic disturbances are important in modeling GIC during strong storms; (2)dB/dtcan vary by several times up to a factor of three compared to the spatial average; (3)dB/dtand its regional variation is coupled to the energy deposited into the magnetosphere; and (4) regional variability can be more accurately captured and predicted from a local index as opposed to a global one. These results demonstrate the need for denser magnetometer networks at high latitudes where transmission lines extending hundreds of kilometers are present. 

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3. 3D Modeling of Geomagnetically Induced Currents in Sweden—Validation and Extreme Event Analysis

   https://doi.org/10.1029/2021SW002988  

   Rosenqvist, L.; Fristedt, T.; Dimmock, A. P.; Davidsson, P.; Fridström, R.; Hall, J. O.; Hesslow, L.; Kjäll, J.; Smirnov, M. Yu; Welling, D.; et al (March 2022, Space Weather)

   Abstract Rosenqvist and Hall (2019),https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018SW002084developed a proof‐of‐concept modeling capability that incorporates a detailed 3D structure of Earth's electrical conductivity in a geomagnetically induced current estimation procedure (GIC‐SMAP). The model was verified based on GIC measurements in northern Sweden. The study showed that southern Sweden is exposed to stronger electric fields due to a combined effect of low crustal conductivity and the influence of the surrounding coast. This study aims at further verifying the model in this region. GIC measurements on a power line at the west coast of southern Sweden are utilized. The location of the transmission line was selected to include coast effects at the ocean‐land interface to investigate the importance of using 3D induction modeling methods. The model is used to quantify the hazard of severe GICs in this particular transmission line by using historic recordings of strong geomagnetic disturbances. To quantify a worst‐case scenario GICs are calculated from modeled magnetic disturbances by the Space Weather Modeling Framework based on estimates for an idealized extreme interplanetary coronal mass ejection. The observed and estimated GIC based on the 3D GIC‐SMAP procedure in the transmission line in southern Sweden are in good agreement. In contrast, 1D methods underestimate GICs by about 50%. The estimated GICs in the studied transmission line exceed 100 A for one of 14 historical geomagnetic storm intervals. The peak GIC during the sudden impulse phase of a “perfect” storm exceeds 300 A but depends on the locality of the station as the interplanetary magnetic cloud hits Earth. 

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4. Modeling the Geomagnetic Response to the September 2017 Space Weather Event Over Fennoscandia Using the Space Weather Modeling Framework: Studying the Impacts of Spatial Resolution

   https://doi.org/10.1029/2020SW002683  

   Dimmock, A. P.; Welling, D. T.; Rosenqvist, L.; Forsyth, C.; Freeman, M. P.; Rae, I. J.; Viljanen, A.; Vandegriff, E.; Boynton, R. J.; Balikhin, M. A.; et al (May 2021, Space Weather)

   Abstract We must be able to predict and mitigate against geomagnetically induced current (GIC) effects to minimize socio‐economic impacts. This study employs the space weather modeling framework (SWMF) to model the geomagnetic response over Fennoscandia to the September 7–8, 2017 event. Of key importance to this study is the effects of spatial resolution in terms of regional forecasts and improved GIC modeling results. Therefore, we ran the model at comparatively low, medium, and high spatial resolutions. The virtual magnetometers from each model run are compared with observations from the IMAGE magnetometer network across various latitudes and over regional‐scales. The virtual magnetometer data from the SWMF are coupled with a local ground conductivity model which is used to calculate the geoelectric field and estimate GICs in a Finnish natural gas pipeline. This investigation has lead to several important results in which higher resolution yielded: (1) more realistic amplitudes and timings of GICs, (2) higher amplitude geomagnetic disturbances across latitudes, and (3) increased regional variations in terms of differences between stations. Despite this, substorms remain a significant challenge to surface magnetic field prediction from global magnetohydrodynamic modeling. For example, in the presence of multiple large substorms, the associated large‐amplitude depressions were not captured, which caused the largest model‐data deviations. The results from this work are of key importance to both modelers and space weather operators. Particularly when the goal is to obtain improved regional forecasts of geomagnetic disturbances and/or more realistic estimates of the geoelectric field. 

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5. Integrating space weather and ground-based magnetotelluric data with powerflow solutions for real-time assessment of risk to the power grid

   Schultz, A (April 2019, https://cpaess.ucar.edu/sites/default/files/documents/2019/2019%20Space%20Weather%20Workshop%20Draft%20Agenda%20with%20Abstracts.pdf)

   The National Space Weather Action Plan, NERC Reliability Standard TPL-007-1,2 associated FERC Orders 779, 830 and subsequent actions, emerging standard TPL-007-3, as well as Executive Order 13744 have prepared the regulatory framework and roadmap for assessing and mitigating the impact on critical infrastructure from space weather. These actions have resulted in an emerging set of benchmarks against which the statistical probability of damage to critical components such as power transmission system high-voltage transformers can be assessed; for the first time the impacts on the intensity of geomagnetically induced currents (GICs) due to the spatial variability of the geomagnetic field and of the Earth’s electrical conductivity structure can be examined systematically. While at present not a strict requirement of the existing reliability standards, there is growing evidence that the strongly three-dimensional nature of the electrical conductivity structure of the North American crust and mantle (heretofore ‘ground conductivity’) has a first-order impact on GIC intensity, with considerable local and regional variability. The strongly location dependent ground electric field intensification and attenuation due to 3-D ground conductivity variations has an equivalent impact on assessment of risk to critical infrastructure due to HEMP (E3 phase) sources of geomagnetic disturbances (GMDs) as it does for natural GMDs. From 2006-2018, Oregon State University (OSU) under NSF EarthScope Program support, installed and acquired ground electric and magnetic field time series (magnetotelluric, or MT) data on a grid of station locations spaced ~70-km apart, at 1161 long-period MT stations covering nearly ⅔ of CONUS. The US Geological Survey completed 47 additional MT stations using functionally identical instrumentation, and the two data sets were merged and made available in the public domain. OSU and its project collaborators have also collected hundreds of wider frequency bandwidth, more densely-spaced MT station data under other project support, and these have been or will be released for public access in the near future. NSF funding was not available to make possible collection of EarthScope MT data 1/3 of CONUS in the southern tier of states, in a band from central California in the west to Alabama in the east and extending along the Gulf Coast and Deep South. OSU, with NASA support just received, plans to complete MT station installation in the remainder of California this year, and with additional support both anticipated and proposed, we hope to complete the MT array in the remainder of CONUS. For this first time this will provide national-scale 3-D electrical conductivity/MT impedance data throughout the US portion of the contiguous North American power grid. Complementary planning and proposal efforts are underway in Canada, including collaborations between OSU, Athabasca University and other Canadian academic and industry groups. In the present work, we apply algorithms we have developed to make use of real-time streams of US Geological Survey, Natural Resources Canada (and other) magnetic observatory data, and the EarthScope and other MT data sets to provide quasi-real time predictions of the geomagnetically induced voltages at high-voltage transmission system transformers/power buses. This goes beyond the statistical benchmarking process currently encapsulated in NERC reliability standards. We seek initially to provide real-time information to power utility control room operators, in the form of a heat map showing which assets are likely experiencing stress due to induced currents. These assessments will be ground-truthed against transmission system sensor data (PMUs, GIC monitors, voltage waveforms and harmonics where available), and by applying machine learning methods we hope to extend this approach to transmission systems that have sparse or non-existent GIC monitoring sensor infrastructure. Ultimately by incorporating predictive models of the geomagnetic field using satellite data as inputs rather than real-time ground magnetic field measurements, a near-term probabilistic assessment of risk to transformers may be possible, ideally providing at least a 15-minute forecast to utility operators. There has been a concerted effort by NOAA to develop a real-time geomagnetically induced ground electric field data product that makes use of our EarthScope MT data, which includes the strong impacts on GICs due to 3-D ground conductivity structure. Both OSU and the USGS have developed methods to determine the GIC-related voltages at substations by integrating the ground electric fields along power transmission line paths. Under National Science Foundation support, the present team of investigators is taking the next step, of applying the GIC-related voltages as inputs to quasi-real time power flow models of the power transmission grid in order to obtain realistic and verifiable predictions of the intensity of induced GICs, the reactive power loss due to GICs, and of GIC effects on the current and voltage waveforms, such as the harmonic distortion. As we work toward integration of predicted induced substation voltages with power flow models, we’ve modified the RTS-GMLC (Reliability Test System Grid Modernization Lab Consortium) test case (https://github.com/GridMod/RTS-GMLC) by moving the geographic location of the case to central Oregon. With the assistance of LANL we have the complete AC and DC network of the RTS-GMLC case, and we are working to integrate the complete case information into Julia (using the PowerModels and PowerModelsGMD packages of LANL), or into PowerWorld. Along a parallel track, we have performed GIC voltage calculations using our geophysical algorithm for a realistic GMD event (Halloween event) for the test case, resulting in GIC transmission line voltages that can be added into our power system model. We’ll discuss our progress in integrating the geophysical estimates of transformer voltages and our DC model using LANL's Julia and PowerModelsGMD package, for power flow simulations on the test case, and to determine the GIC flows and possible impacts on the power waveforms in the system elements. 

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