Maps of extreme value, horizontal component geoelectric field amplitude are constructed for the Pacific Northwest United States (and parts of neighboring Canada). Multidecade long geoelectric field time series are calculated by convolving Earth surface impedance tensors from 71 discrete magnetotelluric survey sites across the region with historical 1‐min (2‐min Nyquist) geomagnetic variation time series obtained from two nearby observatories. After fitting statistical models to 1‐min geoelectric amplitudes realized during magnetic storms, extrapolations are made to estimate threshold amplitudes that are only exceeded, on average, once per century. One hundred‐year geoelectric exceedance amplitudes range from 0.06 V/km at a survey site in western Washington State to 9.47 V/km at a site in southeast British Columbia; 100‐year geoelectric exceedance amplitudes equal 7.10 V/km at a site north of Seattle and 2.28 V/km at a site north of Portland. Systematic and random errors are estimated to be less than 20%, much less than site‐to‐site differences in geoelectric amplitude that arise from site‐to‐site differences in surface impedance. Maps of 100‐year exceedance amplitudes are compared with the peak geoelectric amplitudes realized during the March 1989 magnetic superstorm; it is noted that some storms of relatively modest intensity can generate localized geoelectric fields of relatively high amplitude. The geography of geoelectric hazard across the Pacific Northwest is closely related to known geologic and tectonic structures.

1 Introduction Geomagnetic storms and the geoelectric fields that they induce in the Earth's conducting interior are hazards for high‐voltage electric power grid systems (e.g., Molinski, 2002; Piccinelli & Krausmann, 2014; Samuelsson, 2013). A dramatic realization of these hazards came during the magnetic storm of 13 March 1989 (e.g., Allen et al., 1989) when induced geoelectric fields caused the collapse of the entire Hydro‐Québec power grid system in Canada (Béland & Small, 2005; Bolduc, 2002) and caused operational stress in power grids in the United States (North American Electric Reliability Corporation, 1990 [NERC], 1990). Since then, some researchers have suggested that the future arrival of a rare magnetic superstorm (e.g., Cliver & Dietrich, 2013; Lakhina & Tsurutani, 2018) could cause long‐lasting interruption of electric power transmission (e.g., Kappenman, 2012; Odenwald & Green, 2006)—something that would carry significant economic and societal cost (Baker, 2008; Barnes & Van Dyke, 1990; Eastwood et al., 2017; Lloyd's of London, 2013; Worman et al., 2018). In light of these events and possibilities, the U.S. Federal Energy Regulatory Commission (2013, Order No. 779) directed NERC to assess the vulnerability of U.S. domestic power grid systems to storm time magnetic disturbance. As part of a project to develop benchmarks characterizing extreme space weather events coordinated by the U.S. National Science and Technology Council (2015, Goal 1.1), here we report on an analysis of geoelectric hazards across the state of Washington and surrounding parts of the Pacific Northwest. This region includes the cities of Seattle and Portland, as well as important associated power grid infrastructure that, some have suggested, might be vulnerable to the effects of magnetic storms (Kappenman, 2004, Figure 17). The geomagnetic latitudes of the Pacific Northwest are just south of the auroral zone, and, as a result, local geomagnetic activity can, on occasion, be relatively intense (e.g., Prölss, 2004, chap. 8.3.1), especially during magnetic substorms (e.g., Kamide et al., 1994; McPherron & Manka, 1985). The geology of the region is also complicated (e.g., Chenney, 2016), and the subsurface electrical conductivity structure is both complicated and spatially three‐dimensional (e.g., Bedrosian & Feucht, 2014; Meqbel et al., 2014; Patro & Egbert, 2008). Recognizing all of this and seeking realistic estimates of geoelectric hazards, our analysis is based entirely on data collected from the Pacific Northwest. Using methods similar to those developed by Love, Lucas, et al. (2018) in their analysis of the Mid‐Atlantic United States, we estimate long historical geoelectric field time series calculated for the Northwest by a straightforward empirical method: convolving impedance tensors obtained from various sites during magnetotelluric surveys with geomagnetic time series acquired over decades of time by two magnetic observatories operating in the region. Our statistical analysis allows us to construct maps of geoelectric field amplitudes that are only exceeded, on average, once every 100 years.

2 Induction in the Conducting Earth At the Earth's surface, geomagnetic B(t,x,y) and geoelectric E(t,x,y) field variations are functions of time t and geographic location (north x, east y). For the frequency range of interest here, electromagnetic variation within the Earth can be described in terms of the classical laws of quasi‐static electromagnetism for a conducting medium (e.g., Stratton, 1941, chap. 5). With this, then, and under certain simplifying assumptions that are standard in magnetotelluric science (e.g., Weidelt & Chave, 2012), the convolutional relationship between horizontal component, , geomagnetic, B h =[B x ,B y ], and geoelectric, E h =[E x ,E y ], field variation at a given geographic location can be parameterized in terms of a 2 × 2 impedance tensor that is a function of the Fourier frequency f (period T = 1/f) of sinusoidal variation (e.g., Simpson & Bahr, 2005; Unsworth, 2007; Weidelt & Chave, 2012). Impedance has units of Ω (ohms), and the magnetotelluric impedance tensor is a nonlinear function of subsurface conductivity structure, σ(r) (or, equivalently, subsurface resistivity structure ρ(r) = 1/σ), where r is position within the Earth. Rock conductivity, itself, depends on numerous ancillary properties, including mineralogy, melt and solid phases, water and clay content, porosity, and cracks and grain boundaries (e.g., Evans, 2012; Yoshino, 2011), and, also of relevance, here, is the fact that ocean water is electrically conductive. Qualitatively, field variation is attenuated within the Earth as a diffusive skin effect defined (conventionally) for a frequency‐dependent apparent resistivity (the inverse of apparent conductivity) and corresponding diffusive length scale—resistive (conductive) Earth structure has a long (short) diffusive length scale.

3 Magnetic Observatory Time Series For this analysis, we primarily use 1‐min resolution, definitive B h magnetometer time series acquired at the U.S. Geological Survey Newport (NEW), Washington, magnetic observatory (geographic: 48.27∘N, 117.12∘W; geomagnetic for year 2000: 54.75∘N, 55.72∘W; Love & Finn, 2011; U.S. Geological Survey, 1901) and at the Natural Resources Canada Victoria (VIC), British Columbia, magnetic observatory (geographic: 48.52∘N, 123.42∘W; geomagnetic for year 2000: 54.01∘N, 62.84∘W; Newitt & Coles, 2007); the two observatories are situated on similar geographic and geomagnetic latitudes, but they are separated, mostly in longitude, by 466 km. Vector data from each observatory are recorded as discrete, time‐sequential samples, B h (t i ) for t 1 ,t 2 ,t 3 ,…, with a constant 1min=t i −t i − 1 sampling interval; sinusoidal signals with periods shorter than 2‐min (Nyquist) are suppressed by acquisition process filtering. The time series have been calibrated and cleaned of artificial spikes and offsets. The NEW (VIC) data cover the years 1983–2016 (1977–2016). The 34‐year (40‐year)‐long NEW (VIC) time series is 93.5% (98.2%) complete; there are 16,726,744 (20,659,558) 1‐min geomagnetic vector samples with relatively few gaps. The longest gap in the NEW (VIC) time series is 92 days 00 min (61 days 10 min) in duration, beginning on 1 October 1984, 00:00 UT (30 June 1984 at 00:00 UT); during these gap periods moderate intensity magnetic storms on 16 November 1984 (1 August 1984) were not recorded, maximum −Dst = 141 nT (−Dst = 112 nT). Using 1‐min geomagnetic time series permits estimation of 1‐min resolution geoelectric field variation. It is, however, important to recognize that shorter period (higher‐frequency) geomagnetic signals also contribute to the overall amplitude of the geoelectric variation realized at any particular location. Long‐term collection of 10‐ and 1‐s magnetometer time series only commenced at most magnetic observatories relatively recently; they are not available from either NEW or VIC for the 1989 storm, for example. The NERC (2014) 10‐s resolution benchmark time series, derived by scaling the amplitude of a magnetometer time series of the March 1989 magnetic storm recorded at the Ottawa (OTT), Ontario, magnetic observatory, is sometimes treated as a hypothetical (or scenario) representation of geomagnetic field variation in evaluating geoelectric hazards at locations far removed from Ottawa, including for the Pacific Northwest (e.g., Gannon et al., 2017). However, what is unclear is how well the NERC time series represents the details of geomagnetic field variation at locations other than Ottawa. For our purposes, a short time series recording a single storm is insufficient for the statistical analysis that is the focus of this work. In section 9, we will use a 1‐s NEW and VIC geomagnetic time series (low‐pass filtered to 10 s) of a magnetic storm in 2015 to compare geoelectric amplitudes with those estimated from 1‐min geomagnetic time series. For now, in Figures 1a and 1c, we plot 1‐min NEW and VIC B h (t i ) time series recording the March 1989 magnetic storm, which commenced at 01:28 UT on 13 March and persisted thereafter for about 1.5 days. We note that the NEW time series has a nearly 2‐hr gap that extends from 10:55 to 12:50 UT on 13 March. Storm time disturbance reached a maximum −Dst = 589 nT at 01:30 UT on 14 March (the highest value since 1957, when the Kyoto Dst service was initiated). In Figures 1b and 1d, we plot the minute‐to‐minute differences and ; while the NEW and VIC time series are obviously correlated, differences between the NEW and VIC time series can be about as large as the amplitude of the variation itself. Geomagnetic variation at each observatory is apparently affected by somewhat localized differences in storm time ionospheric current systems. Since these current systems are at heights exceeding 100 km, we can reasonably expect that observatories separated by more than about 100 km might record geomagnetic time series that are different in important ways (e.g., Watermann et al., 2006). How these localized differences in recorded geomagnetic activity affect the calculated geoelectric fields is something we will explore in this report. Figure 1 Open in figure viewer PowerPoint B x (t i ) and (c) east B y (t i ) component geomagnetic field variation recorded at the USGS Newport (NEW, blue), Washington, and NRCan Victoria (VIC, gray), British Columbia, observatories during the magnetic storm of March 1989 and time series (b, d) of corresponding differences and between the NEW and VIC time series. Time series of 1‐min resolution (a) north) and (c) east) component geomagnetic field variation recorded at the USGS Newport (NEW, blue), Washington, and NRCan Victoria (VIC, gray), British Columbia, observatories during the magnetic storm of March 1989 and time series (b, d) of corresponding differencesandbetween the NEW and VIC time series.

4 Magnetotelluric Impedance Tensors For Z, we use 71 magnetotelluric impedance tensors (e.g., Chave & Jones, 2012; Simpson & Bahr, 2005; Unsworth, 2007) constructed (Egbert, 2007) from electromagnetic measurements (e.g., Ferguson, 2012) made at survey sites having a 70‐km nominal spacing in the general vicinity of the NEW and VIC magnetic observatories: 63 of these tensors correspond to survey measurements from across the Pacific Northwest of the United States (Washington, Northern Oregon, Northern Idaho, and Western Montana) made between 2006 and 2008 through the National Science Foundation's EarthScope project (Schultz, 2010; Schultz et al., 2006; Williams et al., 2010); 6 of the sites are from measurements made over a small part of Canada (south‐central British Columbia) made in 2009 through the University of Alberta (Bertrand, 2008); 2 are from the National Science Foundation project known as MOCHA intended for investigation of the Juan de Fuca subduction zone beneath Washington and Oregon (Schultz et al., 2014). Each tensor for each site (x,y) is well defined across a frequency band of 10−4 to 10−1Hz (periods of 10,000 to 10 s) for a discrete set of frequencies, f 1 ,f 2 ,f 3 ,…; errors are estimated to be less than 5% (Schultz, 2010). The EarthScope database includes a quality rating assigned to each tensor (Kelbert et al., 2011): 5 (excellent), 4 (good), 3 (fair), etc.; tensors with quality ratings of 3 or higher are completely suitable for our work here. In Figure 2, we plot apparent resistivities ρ xx (T), ρ xy (T), etc. and phases (of the time the relationship between geomagnetic and geoelectric variations) ϕ xx (T), ϕ xy (T), etc. (e.g., Berdichevsky & Dmitriev, 2008, p. 10) across the period band of 10 to 10,000 s (10−1 to 10−4 Hz) for three magnetotelluric survey sites, denoted WAB10, WAD06, and WAB05, located across the longitudinal breadth of Washington State. For an Earth with a one‐dimensional (1‐D), depth‐dependent conductivity profile, then across all frequencies, ρ xy =ρ yx and ρ xx =ρ yy =0; for a uniform conductivity profile, ϕ xy =ρ yx =45∘ and ϕ xx =ϕ yy =0. That these symmetry properties are not even close to being seen in Figure 2 tells us, right away, that the Earth beneath and surrounding each survey site is far from 1‐D—in fact, generally speaking, the Earth is three‐dimensional (3‐D) in structure. We note, furthermore, that the range in apparent resistivity from one site to another is more than 2 orders of magnitude—this, also, demonstrates the spatial complexity of Earth structure. Figure 2 Open in figure viewer PowerPoint Apparent resistivities and phases, ρ xx (T),ϕ xx (T) (yellow), ρ xy (T),ϕ xy (T) (blue), ρ yx (T),ϕ yx (T) (red), ρ yy (T),ϕ yy (T) (green), together with one standard deviation error bars, each plotted as a function of variational period T, for EarthScope survey sites (a, b) WAB10 (48.26∘N, 117.33∘W), (c, d) WAD06 (47.32∘N, 120.85∘W), and (e, f) WAB05 (48.19∘N, 122.04∘W). In light of Figure 2, we do not use 1‐D surface impedance tensors derived from simple depth‐dependent models of Earth conductivity. Those developed for North America (Blum et al., 2015; Fernberg, 2012; Ferguson & Odwar, 1997) have been used to estimate benchmarks for NERC and in numerous related studies (e.g., Marti et al., 2014; Nikitina et al., 2016; Ngwira et al., 2013; Pulkkinen et al., 2015; Trichtchenko et al., 2016; Wei et al., 2013); indeed, 1‐D models are sometimes treated as first‐order representations of the Earth (e.g., Boteler, 2015; Butala et al., 2017; Gannon et al., 2017; Marti et al., 2014). Despite this, several studies have shown that the use of some 1‐D models (e.g., Fernberg, 2012) can give estimated geoelectric amplitudes that are erroneous by more than an order of magnitude (in some cases, the error exceeds 2 orders of magnitude; e.g., Bedrosian & Love, 2015; Cuttler et al., 2018; Love, Rigler, et al., 2018; Lucas et al., 2018). Furthermore, the magnetotelluric community routinely uses measured impedance tensors, such as those summarized in Figure 2, to construct regional models of subsurface electrical conductivity structure that are far from 1‐D, including for the Pacific Northwest (e.g., Bedrosian & Feucht, 2014; Meqbel et al., 2014; Patro & Egbert, 2008).

5 Geoelectric Time Series As per section 2, we use a computer‐based algorithm (described in Love, Lucas, et al., 2018; Lucas et al., 2018) to calculate 1‐min resolution (band limited: 10−4 to 10−2 Hz) historical geoelectric time series E h (t i ,x,y) from convolution (e.g., Kelbert et al., 2017; Pirjola, 2002; Weigel, 2017) of each magnetotelluric impedance tensor with both of the NEW and VIC geomagnetic time series B h (t i ); we estimate errors of about 20% in the algorithmic calculation of electric fields by comparing them to those measured during the magnetotelluric survey. In Figures 3a and 3c, we plot E h (t i ,x,y) time series for the March 1989 storm for the EarthScope survey site WAD06. Over the course of the storm, we see in Figures 3a and 3c that the geoelectric time series, obtained with NEW and VIC geomagnetic induction, are well correlated. And, furthermore, in comparing Figures 3a and 3c with Figures 1a and 1c we see that geoelectric disturbance levels are generally high (low) when geomagnetic disturbance levels are high (low). In Figures 3b and 3d, we plot minute‐to‐minute differences and for NEW and VIC induction; here we see, as we saw with the geomagnetic time series, that differences in the calculated geoelectric time series can be about as large as the amplitude of the variation itself. Since the geoelectric time series shown in Figure 3 are calculated using the same surface impedance, these differences are entirely due to differences between the NEW and VIC geomagnetic time series. These results are consistent with those of Ngwira et al. (2015), who found that localized differences in geomagnetic activity could give very different induced geoelectric fields for a given impedance tensor. Figure 3 Open in figure viewer PowerPoint E x (t i ) and (c) east E y (t i ) component geoelectric field variation calculated for EarthScope survey site WAD06 for NEW (red) and VIC (gray) geomagnetic induction for the magnetic storm of March 1989; time series (b, d) of corresponding differences and for NEW and VIC induction and (e) time series of horizontal geoelectric amplitude for WAD06 for NEW (red) and VIC (gray) induction; also indicated are the NEW and VIC maximum amplitudes . Time series of 1‐min resolution (a) north) and (c) east) component geoelectric field variation calculated for EarthScope survey site WAD06 for NEW (red) and VIC (gray) geomagnetic induction for the magnetic storm of March 1989; time series (b, d) of corresponding differencesandfor NEW and VIC induction and (e) time series of horizontal geoelectric amplitudefor WAD06 for NEW (red) and VIC (gray) induction; also indicated are the NEW and VIC maximum amplitudes In Figure 3e, we show time series of the horizontal geoelectric amplitude for WAD06 for NEW and VIC geomagnetic induction. Again, correlation between the two time series is obvious, but differences can also be seen. We note that the storm time maximum for the NEW (VIC) time series occurred more than 1 hr apart, 23:23 UT (22:09 UT) on 13 March, with a value of 0.60 V/km (0.69 V/km). For comparison, these (somewhat different) peak times and amplitudes came just after the Bonneville Power Administration (U.S. Pacific Northwest) reports that there was noise at a substation (near Portland) and that capacitors were tripped at four substations and just after the British Columbia Hydro and Power Authority (Canada) reports that their systems experienced significant voltage fluctuations (each at 21:58 UT; North American Electric Reliability Corporation, 1990).

6 Extrapolation to 100‐Year Values We analyze, now, the statistics of our calculated geoelectric field amplitudes. In this context, we note that a hazard can be defined as the probability that a damaging event will occur with size exceeding a threshold, in a specified window of time and located in a specified geographic area (e.g., Smolka, 2006). Following Love, Lucas, et al. (2018), but for our study area of the Pacific Northwest, we analyze the extreme value statistics of the highest 1‐min geoelectric amplitudes, E h (t i ,x,y), at various magnetotelluric survey sites (x,y). We choose to analyze the N largest amplitudes at each site. For consistency between geoelectric time series of different lengths (the NEW time series, 1983–2016, are shorter than those for VIC, 1977–2016); we chose N equal to the number of years in each time series; this leaves us with, on average, one extreme value per year. Next, to extrapolate these amplitudes to extreme values, we need a statistical model. Following on from related work (e.g., Love, Lucas, et al., 2018; Love et al., 2015; Pulkkinen et al., 2008), we examine the hypothesis that extreme value are realized from a lognormal process (e.g., Aitchison & Brown, 1957; Crow & Shimizu, 1988), as we might be generated from the multiplication of numerous random, positive variables describing space weather disturbance and induction in the Earth. Using a maximum‐likelihood algorithm (e.g., James, 2006, chap. 8.3), we fit parameters for a lognormal function to the for each survey site and for NEW (1982–2016) and VIC (1977–2016) induction. In Figure 4, we show the cumulative number of occurrences per year that exceed for survey sites WAB05, WAD06, and WAB10. For both NEW and VIC, geoelectric amplitudes differ significantly from one survey site to another—the difference between the WAB10 and WAB05 values is approximately a factor of 100—this is due to localized differences in impedance (e.g., Bedrosian & Love, 2015; Bonner & Schultz, 2017; McKay & Whaler, 2006), which, themselves, are related to localized differences in Earth conductivity structure. In Figure 4, we also show the cumulatives of fitted lognormal functions, which provide reasonably good representations of the data. The Kolmogorov‐Smirnov p‐value (e.g., James, 2006, chap. 11.4.2) is the probability that the data could have been realized from the hypothetical model; for the lognormal model and the values, p for WAB05 and NEW is 0.43 (VIC, 0.64), for WAD06 and NEW, 0.76 (VIC, 0.93), and for WAB10 and NEW, 0.79 (VIC, 0.72)—for such probabilities, the lognormal hypothesis cannot be rejected. From the fitted lognormal models, we estimate, as extrapolations, geoelectric amplitudes that are exceeded, on average, once every 100 years; in Figure 4, these extrapolations correspond to the intersections of the lognormal functions with the horizontal axis. Figure 4 Open in figure viewer PowerPoint for EarthScope survey sites WAB05, WAD06, and WAB10, each for NEW (1982–2016, red) and VIC (1977–2016, gray) induction, together with fitted lognormal statistical models. The intersections of the models with the horizontal axes, indicated by dots, amount to extrapolated 100‐year threshold values, . Cumulative number of times per year that storm maximum amplitude exceeds the thresholdfor EarthScope survey sites WAB05, WAD06, and WAB10, each for NEW (1982–2016, red) and VIC (1977–2016, gray) induction, together with fitted lognormal statistical models. The intersections of the models with the horizontal axes, indicated by dots, amount to extrapolated 100‐year threshold values,

7 Error Analysis It is important to evaluate the stability of our extrapolations to 100‐year amplitudes—errors are both systematic and random. In Figure 5, we plot for each magnetotelluric survey site obtained using VIC versus NEW induction–that the plotted points tend to fall above the diagonal is representative of the fact that the are systematically slightly higher for VIC induction than for NEW induction. Among the survey sites in the Pacific Northwest, on average, the VIC extrapolations are 1.17 times higher than those for NEW. This difference is small compared to the more than 2 orders of magnitude site‐to‐site range in . To estimate statistical errors, we follow Love, Lucas, et. al. (2018) and use the bootstrap method (e.g., Efron & Tibshirani, 1993). For each survey site and for both NEW and VIC induction, we randomly sample the data with replacement and fit lognormal functions to each sampling, which we then use to extrapolate to (sample) values. From a compilation of such samples, fits, and extrapolations, we obtain confidence intervals for our base 100‐year extrapolations–these are shown as error bars in Figure 5. For all 71 survey sites, we estimate a median m for the 100‐year extrapolation and corresponding lower l and upper u values for a centered 67% confidence interval; for NEW induction [l≃0.90 × m, m, u≃1.11 × m] and VIC [l≃0.84 × m, m, u≃1.19 × m], where m≃ the (original) 100‐year value. Given that the VIC are about 1.33 times higher than those for NEW, we recognize that the 67% confidence intervals are almost overlapping. Figure 5 Open in figure viewer PowerPoint for each of the 71 magnetotelluric survey sites used for the Pacific Northwest and obtained using VIC versus NEW induction; also shown by error bars are bootstrap‐estimated 67% confidence intervals for each site. The 100‐year extrapolated exceedancefor each of the 71 magnetotelluric survey sites used for the Pacific Northwest and obtained using VIC versus NEW induction; also shown by error bars are bootstrap‐estimated 67% confidence intervals for each site.

8 Geoelectric Hazard Maps In Figure 6a, we plot a color‐coded map of extrapolated 100‐year geoelectric exceedance amplitudes for the Pacific Northwest; here in light of the preceding analysis, each geoelectric amplitude time series for each magnetotelluric survey site is calculated using the nearest magnetic observatory (either NEW or VIC). Among the various survey sites, the amplitude is highest at site bc110 in British Columbia at 9.47 V/km, and it is lowest at site WAB10 in eastern Washington at 0.06 V/km. We note that at site WAB05 in western Washington, north of Seattle, is 7.10 V/km, and at site WAF04, north of Portland, Oregon, the amplitude is 2.28 V/km. Across the Pacific Northwest, amplitudes exceed 2 V/km at 6 of the 71 survey sites and exceed 1 V/km at 22 of the 71 sites. For comparison, in Figure 6b, we plot the maximum amplitudes that occurred during the March 1989 magnetic storm (this is not a statistical extrapolation). Only relatively small differences can be seen between Figures 6a and 6b. During the March 1989 storm, exceeded 2 V/km at 5 of the 71 sites considered; it exceeded 1 V/km at 16 of the sites. Figure 6 Open in figure viewer PowerPoint (1‐min resolution) calculated for the various magnetotelluric survey sites across the Pacific Northwest, (b) maximum (1‐min resolution) calculated for the magnetic storm of March 1989, (c) 100‐yr geoelectric exceedance amplitudes for north polarized B x (t) geomagnetic waveforms having a period of 4 min and persisting for a 10‐min duration of time (Love & Bedrosian, 2018). Maps showing (a) 100‐year geoelectric exceedance amplitudes(1‐min resolution) calculated for the various magnetotelluric survey sites across the Pacific Northwest, (b) maximum(1‐min resolution) calculated for the magnetic storm of March 1989, (c) 100‐yr geoelectric exceedance amplitudes for north polarized) geomagnetic waveforms having a period of 4 min and persisting for a 10‐min duration of time (Love & Bedrosian, 2018). In Figure 6c, we compare our hazard estimates with those obtained previously for the continental United States (Love & Bedrosian, 2018; Love et al., 2016). Whereas, we calculate the 1‐min E h analyzed here by convolving geomagnetic time series with magnetotelluric impedances, the hazard maps for the continental United States were indirectly derived: a statistical analysis was performed of historical global geomagnetic variation in terms of the amplitudes of waveforms having specific periods and polarizations and persisting for a given duration of time; the waveforms were convolved with magnetotelluric impedances from various survey sites. These technical distinctions are responsible for our maps of E h amplitudes being, on average, higher than those estimated by Love and Bedrosian (2018). Otherwise, the geographic form of the hazard maps is almost identical; amplitudes are relatively high at WAB05, western Washington; and they are low at WAB10, eastern Washington. Our maps of geoelectric amplitude do not resemble those of Gannon et al. (2017). They report (their section 2.2) selecting tensors having quality ratings of 5 (the highest standard) and that the tensors they use are those shown in their Figure 3. But in our checking of their results, we find that they apparently omitted several tensors with rating 5, and they used several tensors of lower rating (several with ratings of 3 and 4). We consider the use of tensors rated 3 to 5 to be acceptable. In more detail, Gannon et al. (2017) excluded several tensors, for whatever reason, surrounding Seattle down to north of Portland, and yet their contour map (their Figure 4) shows relatively low hazard in this area (where they apparently used no tensors). We find generally high hazard in this area. North of Seattle, Gannon et al. (2017) report (their Figure 3) relatively low hazard at survey site WAB05 (rating 4). We find high hazard at this site. In northwest Montana, they report relatively high hazard at site MTC13 (rating 3). We find only moderate hazard at this site. They report high hazard in northwest Oregon, at site ORF03 (rating 5, their Figure 3, where, for unknown reasons, they plot two vectors). We find only moderate hazard at this site.

9 The 10‐s Versus 1‐min Results As discussed in section 3, our use of 1‐min resolution geomagnetic time series limits our analysis to 1‐min resolution geoelectric time series. As a partial check of the effects of higher‐frequency induction, in Figures 7a and 7c, we show 1‐min and 1‐s geomagnetic field variation B h (t i ) recorded at both NEW and VIC during the storm of 21–24 June 2015 (e.g., Gromova et al., 2016). This storm attained a maximum −Dst = 204 nT, an intensity that is sometimes classified as severe (e.g., Loewe & Prölss, 1997), but what is important, for our purposes, is that it generated significant substorm geomagnetic activity across Pacific Northwest latitudes. Since the magnetotelluric impedance tensors we use are band limited, 10−4 to 10−1 Hz (periods of 10,000 to 10 s), their convolution with the NEW and VIC 1‐s time series give geoelectric time series that are low‐pass filtered to 10 s. In Figures 7b and 7d, we show 1‐min and 10‐s geoelectric amplitude time series E h for NEW induction at the (nearby) survey site WAB10 and VIC induction at the (nearby) survey site WAB05. As might be expected, 10‐s geoelectric time series have higher maximum amplitudes than 1‐min time series. During the June 2015 storm, for NEW‐WAB10, the 1‐min resolution amplitude attained a maximum of 0.0226 V/km, while the maximum 10‐s amplitude was 29% higher of 0.0292; the 1‐min maximum occurred over 10.7 hr after the 10‐s maximum. In contrast, for VIC‐WAB05, the 1 min and 10 s are, respectively, 1.7020 and 1.8822 V/km, a difference of just 11%, and these maxima occurred almost simultaneously. Clearly, site‐to‐site differences in 10‐s and 1‐min geoelectric amplitudes depend on the combination of local geomagnetic activity and Earth impedance. Figure 7 Open in figure viewer PowerPoint B x (t i ) (blue, gray) and east B y (t i ) (green, gray) component geomagnetic field variation recorded at NEW and VIC for the magnetic storm of June 2015 and (b, d) time series of 1‐min (black) and 10‐s (orange) geoelectric amplitude E h (t i ) at EarthScope survey site WAB10 for NEW induction and at WAB05 for VIC induction; also indicated are the 1‐min and 10‐s maximum amplitudes . Time series (a, c) of 1‐min and 1‐s resolution north) (blue, gray) and east) (green, gray) component geomagnetic field variation recorded at NEW and VIC for the magnetic storm of June 2015 and (b, d) time series of 1‐min (black) and 10‐s (orange) geoelectric amplitude) at EarthScope survey site WAB10 for NEW induction and at WAB05 for VIC induction; also indicated are the 1‐min and 10‐s maximum amplitudes In Figure 8, we plot, for the various magnetotelluric survey sites across the Pacific Northwest, 10‐s versus 1‐min maximum amplitudes realized during the June 2015 storm (for induction for the observatory, either NEW or VIC, nearest each survey site). Here we see that the 10‐s amplitudes are systematically higher than the 1‐min amplitudes. The greatest difference is for a 10‐s that is a factor of 3.18 higher than the 1‐min value, but, among the various sites, the 10‐s amplitudes are, on average, 30% higher than 1‐min amplitudes. We suppose that whether or not this difference can be regarded as significant depends on the application, but we note that differences seen in Figure 8 are much smaller than 2 orders of magnitude range in amplitudes seen from one site to another. Figure 8 Open in figure viewer PowerPoint realized during the magnetic storm of June 2015 for each of the 71 magnetotelluric survey sites used for the Pacific Northwest (for induction for the observatory, either NEW or VIC, nearest each survey site). The 10‐s versus 1‐min maximum amplitudesrealized during the magnetic storm of June 2015 for each of the 71 magnetotelluric survey sites used for the Pacific Northwest (for induction for the observatory, either NEW or VIC, nearest each survey site).

10 Lists of Extreme Geoelectric Events In Table 1, we list dates for the 10 highest geoelectric events , together with peak −Dst values, for three survey sites (WAB05, WAD06, and WAB10) and for the nearest magnetic observatory (either NEW or VIC). The lists are not identical. While, at all three sites, the March 1989 magnetic storm (maximum −Dst = 589 nT) generated high‐amplitude geoelectric fields, the highest amplitudes over the duration of each observatory time series were realized for other magnetic storms; for WAB05‐VIC, the relatively modest storm of 12 September 1986 (maximum −Dst = 170 nT) actually generated higher‐amplitude geoelectric fields than the March 1989 storm. In contrast to these results for the Pacific Northwest, Love, Lucas, et al. (2018) found that the March 1989 storm gave the highest geoelectric amplitudes across most of the (lower‐latitude) Mid‐Atlantic region. We speculate that proximity of the Pacific Northwest to ionospheric electric currents of the auroral zone generates intense geomagnetic activity (and can, at some places on the Earth's surface, induce high‐amplitude geoelectric fields), even during storms of moderate Dst. This means that Dst is not an especially good index for predicting the occurrence of extreme value geoelectric amplitudes at auroral latitudes. Table 1. Ten Largest E Values for Three Different Magnetotelluric Sites: WAB05 and WAD06 for VIC Geomagnetic Induction (1977‐2016) and WAB10 for NEW Geomagnetic Induction (1983‐2016). Also Given Are the Maximum Storm Time‐Dst Values WAB05 (VIC: 1973‐2016) WAD06 (VIC: 1973‐2016) WAB10 (NEW: 1983‐2016) E ‐Dst E ‐Dst E ‐Dst Rank Year Month Day (V/km) (nT) Year Month Day (V/km) (nT) Year Month Day (V/km) (nT) 1 1981 4 13 5.6543 311 1981 4 13 0.7155 311 1992 2 21 0.0528 174 2 1982 7 14 5.3289 325 1989 3 13 0.6871 589 1999 10 22 0.0495 237 3 1994 4 17 3.9983 201 1982 7 13 0.5934 325 1989 3 13 0.0475 589 4 1986 9 12 3.9256 170 1982 9 6 0.5409 289 1998 9 25 0.0474 207 5 1992 2 21 3.7796 201 1998 9 25 0.5320 207 1992 5 10 0.0447 288 6 2000 7 15 3.5924 301 1989 10 21 0.5208 268 2000 7 15 0.0421 301 7 1982 9 6 3.5832 289 1992 5 10 0.4821 288 2001 4 18 0.0420 114 8 1992 5 10 3.3850 288 2005 5 15 0.4733 247 1991 10 28 0.0411 354 9 1989 3 14 3.1613 589 1978 8 28 0.4253 226 2000 4 7 0.0405 288 10 2005 5 15 2.9401 207 1986 9 12 0.4036 170 1994 4 17 0.0390 201

11 The Geological Context The geology of the Pacific Northwest, see Figure 9, is an amalgam of Earth history (e.g., Oldow et al., 1989), and geology is the primary factor affecting the site‐to‐site geographic differences in the geoelectric hazards seen in Figure 6. Throughout the past 2 billion years, continental rifting has repeatedly torn North America apart, while subduction has accreted various continental fragments and island arc terranes to form the patchwork seen today. The scars and sutures left behind by these tectonic processes are reflected in the electrical resistivity of the crust and mantle lithosphere. The low geoelectric hazards in northwest Montana, northern Idaho, and northeastern Washington, like at survey site WAB10, are related to the Belt Basin, a (1.5 Ga) failed rift filled with a thick sequence of sedimentary rock (e.g., Bedrosian & Box, 2016). For 2‐min geomagnetic variation (Nyquist for the data analyzed here), the apparent conductivity at WAB10 is 0.2 S/m, corresponding to a diffusive skin depth of 12 km, well within conductive basin rocks extending tens of kilometers in depth (e.g., Bedrosian & Box, 2016, Figure 3). High‐hazard regions commonly occur over resistive igneous and metamorphic rocks. The western margin of the Belt Basin, for example, is overprinted by a series of 100‐Ma granitic intrusions as well as a series of metamorphic core complexes—rocks exhumed from deep in the crust. This region includes high‐hazard sites in southeast British Columbia, including bc110. Similarly, a northwest trending band of high geoelectric hazard in eastern Washington and Idaho, including site WAD10, is related to the Pend d'Oreille block, argued to be a continental fragment in part because its resistive signature extends from the surface to more than 150‐km depth (Bedrosian & Feucht, 2014). High geoelectric hazards in Northwest Washington, including site WAB05, are situated atop the southern tip of the Coast Plutonic Complex, the intrusive core of an ancient mountain belt that stretches for nearly 2,000 km along the western edge of Canada. Finally, a north‐south band of high geoelectric hazard extends from WAB05 (north of Seattle) down to WAF04 (north of Portland), following the Siletz Terrane, a large igneous province that accreted to the North American margin 50 Ma (e.g., Wells et al., 2014). Localized geoelectric hazards, even at the spatial granularity of a single site, also reflect geologic structure. The low‐hazard site WAE05, near Mount Rainier and Mount St. Helens, sits atop a prominent crustal conductor, mineralized metasedimentary rocks wedged between the Siletz Terrane and the older North American margin (e.g., Stanley et al., 1987). Relatively lower geoelectric hazards along the Olympic Peninsula are related to a subduction complex—conductive ocean floor sediments scraped off the subducting plate and accreted to the North American margin (Aprea et al., 1998). Figure 9 Open in figure viewer PowerPoint Map of geological features affecting geoelectric hazards across the Pacific Northwest (amplitude of 100‐year exceedances are shown). Resistive (conductive) geologic features are shown in red (blue) shading. Resistive units include the following: the Siletz Terrane (ST), a large igneous province that runs along the Washington and Oregon coast; the Pend O'reille block (POB), a continental fragment extending to depths in excess of 150 km; the Coast Plutonic Complex (CPC), the intrusive core of an ancient mountain belt that stretches into Canada; and a belt of intrusive and metamorphic rocks (IM) in southeastern British Columbia. Conductive units include the following: the Olympic Mountains (OM), ocean floor sediments scraped off the subducting plate and accreted to the North American margin; the Belt Basin (BB), a deep rift basin filled with sedimentary rocks containing disseminated metallic sulfides; and the Southern Washington Crustal Conductor (SWCC), metasedimentary rocks wedged between the Siletz Terrane and the older North American margin. What is not apparent in Figure 6 is a coast effect (e.g., Lilley, 2007; Pirjola, 2013), in which geoelectric fields are amplified or attenuated in proximity to the prominent conductivity contrast between the continent and ocean. Near a coast, induction depends on the polarization of geomagnetic variation. If it is perpendicular to a coastline, induced geoelectric fields on land that are attenuated (typically over a distance of several hundred kilometers from the coast); if geomagnetic variation is parallel to the coastline, induced geoelectric fields are amplified over much shorter distances (typically tens of kilometers). Noting that our analysis, here, is focused on the extreme value geoelectric intensity, the coast effect would likely be more readily manifest in analyses that focus on the directionality of geoelectric field variation (e.g., Rippe et al., 2013), possibly utilizing magnetotelluric tensors acquired with survey station space shorter than the 70‐km spacing of the EarthScope survey.

12 Concluding Discussion This work highlights the importance of both long‐term geomagnetic monitoring and modern magnetotelluric surveys for making realistic assessments of geoelectric hazards of concern to the electric power grid industry. For regions where either geomagnetic monitoring data or magnetotelluric survey data are unavailable, realistic assessments of geoelectric hazards cannot be performed—physics‐based models of magnetic storms and models of solid‐Earth conductivity structure need to be rigorously validated against data of the very same type used in this analysis, and when those data are available, they might as well be directly used. Looking beyond the statistical hazard maps developed here, a related follow‐on project would be the development of time series scenario maps for individual magnetic storms—convolving time‐varying maps of ground‐level geomagnetic disturbance, derived from ground‐based magnetometer data (e.g., Pulkkinen et al., 2003; Rigler et al., 2014), with maps of Earth‐surface impedance, derived from a model of Earth conductivity, which, itself, is based on magnetotelluric survey data. One can imagine that such a project could be further developed into a real‐time service, though the challenges are considerable (e.g., Love, Rigler, et al., 2018). Additional geomagnetic monitoring stations and denser magnetotelluric surveying, both in the United States and in southern Canada, would lead to improved geoelectric hazard mapping needed to assess the vulnerability of the greater integrated North American electric power grid network.

Acknowledgments We thank M. F. Diggles, C. A. Finn, J. L. Gannon, J. McCarthy, E. J. Rigler, and two anonymous persons for reviewing a draft manuscript. This work was supported by the USGS Geomagnetism Program; G. M. Lucas is supported by the USGS Mendenhall postdoctoral fellowship. The NEW magnetic observatory data used in this report are available from the USGS Geomagnetism Program (www.usgs.gov); 1983–2016; the VIC data are available from the NRCan Geomagnetism Program (www.geomag.nrcan.gc.ca; 1977–2016 www.geomag.nrcan.gc.ca; 1977–2016); some of the observatory data can be obtained from INTERMAGNET (www.intermagnet.org; 1991–2016 www.intermagnet.org; 1991–2016). The EarthScope and University of Alberta impedance tensors used in this report can be obtained from the Data Management Center of the Incorporated Research Institutions for Seismology (ds.iris.edu/ds/products/emtf) (Kelbert et al., 2011).