Geology topics

E. Joshua Rigler

Publications and source records attributed to E. Joshua Rigler.

29 records · Page 2Linked to original sources

USGS2020

A 100-year geoelectric hazard analysis for the U.S. high-voltage power grid

A once-per-century geoelectric hazard map is created for the United States high-voltage power grid. A statistical extrapolation from 31 years of magnetic field measurements is made by identifying 84 geomagnetic storms with the Kp and Dst indices. Data from 24 geomagnetic observatories, 1079 magnetotelluric survey sites, and 17,258 transmission lines are utilized to perform a geoelectric hazard analysis with the most comprehensive data publicly available. With this data we estimate once-per-century geoelectric fields at the magnetotelluric survey sites and calculate the theoretical voltages within transmission lines in the United States power grid. Once-per-century geoelectric field strengths span more than three orders of magnitude from a minimum of 0.02 V/km at a site in Idaho to a maximum of 26.8 V/km at a site in Maine, with nearly 30% of the surveyed land area ex- ceeding 1 V/km. We show the influence that geoelectric field polarization has on geoelec- tric hazards when viewed on a power transmission network. The calculated transmission line voltages can exceed 1000 V in some transmission lines. Four regions in the United States with particularly notable geoelectric hazards are identified and discussed: the East coast, Pacific Northwest, upper Midwest, and the Denver metropolitan area.

Space Weather↗

USGS2018

On the feasibility of real-time mapping of the geoelectric field across North America

A review is given of the present feasibility for accurately mapping geoelectric fields across North America in near-realtime by modeling geomagnetic monitoring and magnetotelluric survey data. Should this capability be successfully developed, it could inform utility companies of magnetic-storm interference on electric-power-grid systems. That real-time mapping of geoelectric fields is a challenge is reflective of (1) the spatiotemporal complexity of geomagnetic variation, especially during magnetic storms, (2) the sparse distribution of ground-based geomagnetic monitoring stations that report data in realtime, (3) the spatial complexity of three-dimensional solid-Earth impedance, and (4) the geographically incomplete state of continental-scale magnetotelluric surveys.

Open-File Report↗

USGS2018

Operational nowcasting of electron flux levels in the outer zone of Earth's radiation belt

We describe a lightweight, accurate nowcasting model for electron flux levels measured by the Van Allen probes. Largely motivated by Rigler et al. ( 2004 , https://doi.org/10.1029/2003SW000036 ), we turn to a time‐varying linear filter of previous flux levels and K p . We train and test this model on data gathered from the 2.10 MeV channel of the Relativistic Electron‐Proton Telescope sensor onboard the Van Allen probes. Dynamic linear models are a specific case of state space models and can be made flexible enough to emulate the nonlinear behavior of particle fluxes within the radiation belts. Real‐time estimation of the parameters of the model is done using a Kalman filter, where the state of the model is exactly the parameters. Nowcast performance is assessed against several baseline interpolation schemes. Our model demonstrates significant improvements in performance over persistence nowcasting. In particular, during times of high geomagnetic activity, our model is able to attain performance substantially better than a persistence model. In addition, residual analysis is conducted in order to assess model fit and to suggest future improvements to the model.

Space Weather↗

USGS2017

Methodology for time-domain estimation of storm time geoelectric fields using the 3-D magnetotelluric response tensors

Geoelectric fields at the Earth's surface caused by magnetic storms constitute a hazard to the operation of electric power grids and related infrastructure. The ability to estimate these geoelectric fields in close to real time and provide local predictions would better equip the industry to mitigate negative impacts on their operations. Here we report progress toward this goal: development of robust algorithms that convolve a magnetic storm time series with a frequency domain impedance for a realistic three-dimensional (3-D) Earth, to estimate the local, storm time geoelectric field. Both frequency domain and time domain approaches are presented and validated against storm time geoelectric field data measured in Japan. The methods are then compared in the context of a real-time application.

Space Weather↗

USGS2017

Time-causal decomposition of geomagnetic time series into secular variation, solar quiet, and disturbance signals

A theoretical basis and prototype numerical algorithm are provided that decompose regular time series of geomagnetic observations into three components: secular variation; solar quiet, and disturbance. Respectively, these three components correspond roughly to slow changes in the Earth’s internal magnetic field, periodic daily variations caused by quasi-stationary (with respect to the sun) electrical current systems in the Earth’s magnetosphere, and episodic perturbations to the geomagnetic baseline that are typically driven by fluctuations in a solar wind that interacts electromagnetically with the Earth’s magnetosphere. In contrast to similar algorithms applied to geomagnetic data in the past, this one addresses the issue of real time data acquisition directly by applying a time-causal, exponential smoother with “seasonal corrections” to the data as soon as they become available.

Open-File Report↗

USGS2015

A one-dimensional model of solid-earth electrical resistivity beneath Florida

An estimated one-dimensional layered model of electrical resistivity beneath Florida was developed from published geological and geophysical information. The resistivity of each layer is represented by plausible upper and lower bounds as well as a geometric mean resistivity. Corresponding impedance transfer functions, Schmucker-Weidelt transfer functions, apparent resistivity, and phase responses are calculated for inducing geomagnetic frequencies ranging from 10 −5 to 100 hertz. The resulting one-dimensional model and response functions can be used to make general estimates of time-varying electric fields associated with geomagnetic storms such as might represent induction hazards for electric-power grid operation. The plausible upper- and lower-bound resistivity structures show the uncertainty, giving a wide range of plausible time-varying electric fields.

Florida↗

USGS2015

On the lognormality of historical magnetic-storm intensity statistics: Implications for extreme-event probabilities

An examination is made of the hypothesis that the statistics of magnetic storm maximum intensities are the realization of a lognormal stochastic process. Weighted least squares and maximum likelihood methods are used to fit lognormal functions to − D s t storm time maxima for years 1957–2012; bootstrap analysis is used to established confidence limits on forecasts. Both methods provide fits that are reasonably consistent with the data; both methods also provide fits that are superior to those that can be made with a power‐law function. In general, the maximum likelihood method provides forecasts having tighter confidence intervals than those provided by weighted least squares. From extrapolation of maximum likelihood fits: a magnetic storm with intensity exceeding that of the 1859 Carrington event, − D s t ≥ 850 nT, occurs about 1.13 times per century and a wide 95% confidence interval of [0.42, 2.41] times per century; a 100 year magnetic storm is identified as having a − D s t ≥ 880 nT (greater than Carrington) but a wide 95% confidence interval of [490, 1187] nT.

Geophysical Research Letters↗

USGS2015

Real-time validation of the Dst Predictor model

The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reﬂect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Deﬁnitive Dst is the reference index (Section 3). Whether or not the model better reﬂects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Deﬁnitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efﬁciency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor. Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certiﬁed requirements makes further recommendations difﬁcult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine such requirements. Nowcast persistence is often hard to beat for short term forecasts and speciﬁcation and Dst Predictor clearly performs well against that standard (with 1-hour and 4-hour skill-scores of 0.233 and 0.485 respectively), although poor in absolute terms (with1-hourand4-hour prediction efﬁciencies of-64.6and-43.1, respectively).

Air Force Research Laboratory Technical Report↗

USGS2014

Magnetic storms and induction hazards

Magnetic storms are potentially hazardous to the activities and technological infrastructure of modern civilization. This reality was dramatically demonstrated during the great magnetic storm of March 1989, when surface geoelectric fields, produced by the interaction of the time-varying geomagnetic field with the Earth's electrically conducting interior, coupled onto the overlying Hydro-Québec electric power grid in Canada. Protective relays were tripped, the grid collapsed, and about 9 million people were temporarily left without electricity [ Bolduc , 2002].

Eos, Earth and Space Science News↗

USGS2012

Solar thematic maps for space weather operations

Thematic maps are arrays of labels, or "themes", associated with discrete locations in space and time. Borrowing heavily from the terrestrial remote sensing discipline, a numerical technique based on Bayes' theorem captures operational expertise in the form of trained theme statistics, then uses this to automatically assign labels to solar image pixels. Ultimately, regular thematic maps of the solar corona will be generated from high-cadence, high-resolution SUVI images, the solar ultraviolet imager slated to fly on NOAA's next-generation GOES-R series of satellites starting ~2016. These thematic maps will not only provide quicker, more consistent synoptic views of the sun for space weather forecasters, but digital thematic pixel masks (e.g., coronal hole, active region, flare, etc.), necessary for a new generation of operational solar data products, will be generated. This paper presents the mathematical underpinnings of our thematic mapper, as well as some practical algorithmic considerations. Then, using images from the Solar Dynamics Observatory (SDO) Advanced Imaging Array (AIA) as test data, it presents results from validation experiments designed to ascertain the robustness of the technique with respect to differing expert opinions and changing solar conditions.

Space Weather↗

USGS2012

Sunspot random walk and 22-year variation

We examine two stochastic models for consistency with observed long-term secular trends in sunspot number and a faint, but semi-persistent, 22-yr signal: (1) a null hypothesis, a simple one-parameter random-walk model of sunspot-number cycle-to-cycle change, and, (2) an alternative hypothesis, a two-parameter random-walk model with an imposed 22-yr alternating amplitude. The observed secular trend in sunspots, seen from solar cycle 5 to 23, would not be an unlikely result of the accumulation of multiple random-walk steps. Statistical tests show that a 22-yr signal can be resolved in historical sunspot data; that is, the probability is low that it would be realized from random data. On the other hand, the 22-yr signal has a small amplitude compared to random variation, and so it has a relatively small effect on sunspot predictions. Many published predictions for cycle 24 sunspots fall within the dispersion of previous cycle-to-cycle sunspot differences. The probability is low that the Sun will, with the accumulation of random steps over the next few cycles, walk down to a Dalton-like minimum. Our models support published interpretations of sunspot secular variation and 22-yr variation resulting from cycle-to-cycle accumulation of dynamo-generated magnetic energy.

Geophysical Research Letters↗