Geomagnetically Induced Currents Modeling and Forecasting
2015; American Geophysical Union; Volume: 13; Issue: 11 Linguagem: Inglês
10.1002/2015sw001316
ISSN1542-7390
Autores Tópico(s)Geomagnetism and Paleomagnetism Studies
ResumoSpace WeatherVolume 13, Issue 11 p. 734-736 CommentaryFree Access Geomagnetically Induced Currents Modeling and Forecasting Antti Pulkkinen, Corresponding Author Antti PulkkinenSearch for more papers by this author Antti Pulkkinen, Corresponding Author Antti PulkkinenSearch for more papers by this author First published: 19 October 2015 https://doi.org/10.1002/2015SW001316Citations: 20AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Background Significant progress has been made in understanding the physics, modeling, forecasting, applications, engineering, and regulatory dimensions of geomagnetically induced currents (GIC) over the past decades. This collection demonstrates the evolution of the field over these decades. In this brief commentary I provide some personal observations about modeling and forecasting dimension of the field. Physics-based modeling and forecasting is the ultimate test for our understanding of any natural phenomenon. In the GIC context, the test is a very challenging one. GIC can be viewed as the end link of the space weather chain from the solar atmosphere down to the upper mantle of the Earth; the GIC signal measured, for example, at high-voltage power transformer neutrals carries information about all the physical processes along the chain. This is analogous to stock markets where the value of individual indices such as National Association of Securities Dealers Automated Quotations (NASDAQ) is an aggregate of processes operating at multiple different temporal and "spatial" scales resulting in an incredibly complex signal at the end. We see similar complexity in the GIC signal. This complexity poses very interesting challenges for our understanding of the physics of GIC and modeling of the phenomenon. From the societal standpoint, accurate modeling of the GIC phenomenon is needed for both hazards assessments and execution of active mitigation procedures. More specifically, robust modeling of the geoelectric field is required for any rigorous GIC impacts analyses that involve detailed quantification of possible deleterious effects on systems such as oil pipelines, power transmission, and railway systems. One of the common questions asked by the end-users is "how bad can it get?" Given the complexity of the system, physics-based modeling of the GIC phenomenon is required for probing such questions. If the key physical processes responsible for GIC are captured accurately and the fundamental physics of the system do not change under extreme driving, it is feasible to use physics-based models to explore theoretical extremes. However, one needs to be careful in evaluating the applicability of individual modeling approaches to address the extremes. It is possible that fundamental approximations associated with, for example, single-fluid magnetohydrodynamic (MHD) simulations become significant limitations under extreme driving conditions. The analyses of extremes are the fundamental piece in our quest to explore the "how bad can it get?" questions. In the absence of extended, several-hundreds-of-years-long observational records, modeling of extremes will most likely play an increasingly important role in studies of GIC. In addition to studies of extremes, modeling can be used to elevate the situational awareness on a continuous basis. Advance information or forecasts about pending events are the key for active natural hazards mitigation procedures. In the GIC context, a variety of actions can be carried out if reliable information about the incoming event is available. In the high-voltage electric power transmission context, actions range from postponing maintenance of critical lines to deployment of reserve power for making the system more stable while weathering the storm [e.g., Molinski, 2002]. However, the selection of an appropriate response requires actionable information (i.e., reliable information presented in a form understandable by, and useful to, operations teams). Mitigation actions can be costly for the operator and appropriate action is not possible without good understanding of the quality of information provided. Developing detailed understanding of the end-user needs (see Pulkkinen et al. [2015b] for a recent interagency effort to develop this kind of understanding) and making forecasted GIC information actionable are some of the primary challenges for the space weather modeling and forecasting community. Finally, for inherently interdisciplinary topics such as GIC, a multidisciplinary approach is required for addressing the problem. One of the greatest advancements in the GIC field over the past years has been the establishment of a common language between the space weather science and power engineering communities. In the U.S., much of the recent multidisciplinary communications has been facilitated through the North American Reliability Corporation's Geomagnetic Disturbances Task Force. Space weather scientists now know what engineers need for impact assessments and engineers know what to ask from the scientists. In most cases, the geoelectric field that drives GIC has been established as the physical interface between the science and power engineering communities. The task for space weather scientists is to characterize the spatiotemporal evolution of the geoelectric field in the past, present, and future and do so as accurately as possible. Past and Present Our understanding of the basic physical principles behind GIC builds on our understanding of the space plasma and terrestrial electromagnetic induction processes. While the GIC problem has its own set of specific challenges, progress in these fields often has direct implications also for progress in understanding GIC. We now know that the dynamic electric currents occupying the solar wind-magnetosphere-ionosphere domains cause geomagnetic variations and the dynamic conditions are controlled by the interaction between the Earth's magnetosphere and interplanetary structures and transients such as coronal mass ejections. Geomagnetic variations generate a surface geoelectric field via the electromagnetic induction process. The geoelectric field in turn drives GIC, which is the fundamental reason why the geoelectric field serves as the key interface between the scientific and engineering communities [e.g., Bernabeu, 2012]. Advances in GIC modeling reflect the advances in space plasma and electromagnetic induction modeling. Basic electromagnetic induction modeling tools such as the extensively applied plane wave method have been used successfully in GIC studies for decades. It is generally understood that if the local total (external and internal) geomagnetic field variations and effective local one-dimensional (1-D) ground conductivity are known, in many situations one can model the corresponding geoelectric field using the plane wave method with sufficient accuracy. Also, empirical methods for predicting geomagnetic field variations from driving solar wind conditions have been developed and are available for GIC research purposes [e.g., Weigel et al., 2003; Wintoft, 2005; Weimer, 2013]. However, there has been a recent breakthrough in how we can apply modern physics-based space plasma simulations in GIC research [e.g., Zhang et al., 2012; Ngwira et al., 2014]. These advances have allowed development of novel forecasting techniques and exploration of theoretical extremes of GIC. The relative maturity of the empirical and physics-based modeling capacity is demonstrated in community-wide validation efforts and in transitioning of one of the major global magnetospheric MHD models to operations at NOAA Space Weather Prediction Center (SWPC). One of the primary uses of the new modeling capacity at NOAA SWPC is to provide advanced forecasting services for the power grid industry. Once spatiotemporal evolution of the geoelectric field has been specified, it is quite straightforward to compute GIC flow if direct current (DC) characteristics of the system are known [Lehtinen and Pirjola, 1985; Boteler and Pirjola, 2014]. What has been critically important for quantifying the impact on the power grids is the development of new engineering models. The engineering models allow quantitative considerations such as power grid voltage stability, harmonics, and transformer heating due to known GIC distribution. These analysis tools are now also available commercially, allowing comprehensive hazards analyses on any high-voltage power transmission system of interest. Such hazards analyses are the core element of the standards being developed in the U.S. in response to the Federal Energy Regulatory Commission's Order no. 779 [United States of America Federal Energy Regulatory Commission, 2013]. Future Challenges While significant progress has been made in modeling and forecasting GIC, a number of interesting challenges lie ahead. The classic 1-D electromagnetic induction modeling that has been used successfully for decades in GIC research has its limitations. The true local geology is generally not 1-D. Severe 2-D or 3-D electromagnetic effects can be experienced in areas of sharp lateral gradients in ground conductivity, such as at ocean-land boundaries. Consequently, one of the next steps in geoelectric field and GIC modeling is to evaluate the situations where the 1-D modeling fails and consider the usage of 3-D modeling in the corresponding conditions. Toward this end, the electromagnetic induction community has developed 3-D models that in principle are ready for use also in GIC research. However, work is needed to build the bridges that allow execution of 3-D induction models with the data from modern space physics analyses such as global magnetospheric MHD model output. Similar advancements are needed in mapping of the detailed 3-D ground conductivity structures across the regions of interest. These mapping efforts are underway. For example, the EarthScope project targets the derivation of the 3-D ground structures across the contiguous U.S. (http://www.earthscope.org). Completion of this effort is highly desirable for the next generation U.S. GIC research efforts. The "holy grail" of space weather predictions, namely, modeling of interplanetary magnetic field (IMF) evolution at Earth in association with coronal mass ejections, pertains also to GIC. The IMF specification would allow geomagnetic storm strength predictions with a 1–3 day lead time. However, in the GIC context it is not sufficient to capture only the overall average features of the IMF. Since turbulent IMF features are known to be one of the major drivers of GIC [Huttunen et al., 2008], it is necessary to capture also the smaller scale interplanetary structures responsible for GIC. This requirement poses another significant challenge for the space weather modeling community and may require use of techniques such as statistical downscaling (familiar from applications in the terrestrial weather community) to represent IMF fluctuations [Owens et al., 2014]. Another example of future challenges pertains to recent discovery of the role small spatial-scale (~100 km) ionospheric features play in generating extreme geoelectric fields [Pulkkinen et al., 2015a; Ngwira et al., 2015]. While small spatial-scale ionospheric features appear to play a significant role in driving extreme geoelectric fields, it is not yet clear what solar wind-magnetosphere-ionosphere processes are responsible for these features. It also is not clear if current global MHD models are capable of producing such features and it is possible that more advanced modeling techniques incorporating kinetic plasma processes may be needed. From the GIC impacts standpoint, the question about scales is important as different geoelectric field spatial scales have different implications for performance of the bulk power system. For example, spatially localized extreme geoelectric field features are thought to pose smaller risk than larger-scale enhancements for the stability and health of the bulk power transmission system. Major progress has been made in understanding GIC over the past decades, and the field is mature enough to allow quantification of the physical processes and impacts in guiding the mitigation of the hazard. However, we need to keep pushing forward. GIC are one of the ultimate tests of our capacity to understand and model the entire space weather chain; the real quantifiable impacts of the phenomenon pose a societally relevant challenge for physicists, engineers, and policy makers. Multidisciplinary physics-based investigations with well-defined interfaces between disciplines need to continue to further our modeling and forecasting of GIC. The societal relevance of GIC has drawn a growing number of talented researchers to work on the problem, and the future of the field looks very bright. I look forward to reading about this new GIC research from American Geophysical Union Space Weather Journal and other international publications. Biography Antti Pulkkinen is Research Astrophysicist and the Director of NASA Goddard Space Flight Center Space Weather Research Center in Greenbelt, MD. E-mail: antti.a.pulkkinen@nasa.gov. References Bernabeu, E. 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Fugate, W. Jacobs, and I. Honkonen (2015b), Solar storm GIC forecasting: Solar shield extension—Development of the end-user forecasting system requirements, Space Weather, doi:10.1002/2015SW001283. United States of America Federal Energy Regulatory Commission (2013), Reliability standards for geomagnetic disturbances, Order 779, 16 May. [Available at https://www.ferc.gov/whats-new/comm-meet/2013/051613/E-5.pdf.] Weigel, R. S., Klimas, A. J., and Vassiliadis, D. (2003), Solar wind coupling to and predictability of ground magnetic fields and their time derivatives, J. Geophys. Res., 108(A7), 1298, doi:10.1029/2002JA009627. Weimer, D. R. (2013), An empirical model of ground-level geomagnetic perturbations, Space Weather, 11, 107– 120, doi:10.1002/swe.20030. Wintoft, P. (2005), Study of solar wind coupling to the time difference horizontal geomagnetic field, Ann. Geophys., 23, 1949– 1957. Zhang, J. J., C. Wang, and B. B. Tang (2012), Modeling geomagnetically induced electric field and currents by combining a global MHD model with a local one-dimensional method, Space Weather, 10, S05005, doi:10.1029/2012SW000772. Citing Literature Volume13, Issue11November 2015Pages 734-736 This article also appears in:Commentaries on Atmospheric SciencesCommentaries on Space Weather and Space PhysicsGeomagnetically Induced Currents: Commentary and ResearchVol. 13, Issue 1 ReferencesRelatedInformation
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