Efficient analysis and representation of geophysical processes using localized spherical basis functions

While many geological and geophysical processes such as the melting of icecaps, the magnetic expression of bodies emplaced in the Earth's crust, or the surface displacement remaining after large earthquakes are spatially localized, many of these naturally admit spectral representations, or they may need to be extracted from data collected globally, e.g. by satellites that circumnavigate the Earth. Wavelets are often used to study such nonstationary processes. On the sphere, however, many of the known constructions are somewhat limited. And in particular, the notion of `dilation' is hard to reconcile with the concept of a geological region with fixed boundaries being responsible for generating the signals to be analyzed. Here, we build on our previous work on localized spherical analysis using an approach that is firmly rooted in spherical harmonics. We construct, by quadratic optimization, a set of bandlimited functions that have the majority of their energy concentrated in an arbitrary subdomain of the unit sphere. The `spherical Slepian basis' that results provides a convenient way for the analysis and representation of geophysical signals, as we show by example. We highlight the connections to sparsity by showing that many geophysical processes are sparse in the Slepian basis.Comment: To appear in the Proceedings of the SPIE, as part of the Wavelets XIII conference in San Diego, August 200

Spatial Distribution of Volcanic Hotspots and Paterae on Io: Implications for Tidal Heating Models and Magmatic Pathways

Io, the innermost of Jupiter's Galilean satellites, is the most volcanically active body in the Solar. System. Io's global mean heat flow is approximately 2 W/square m, which is approximately 20 times larger than on Earth. High surface temperatures concentrate within "hotspots" and, to date, 172 Ionian hotspots have been identified by spacecraft and Earth-based telescopes. The Laplace resonance between Io, Europa, and Ganymede maintains these satellites in noncircular orbits and causes displacement of their tidal bulges as the overhead position of Jupiter changes for each moon. Gravitational interactions between Jupiter and Io dominate the orbital evolution of the Laplacian system and generate enormous heat within to as tidal energy is dissipated. If this energy were transferred out of Io at the same rate as it is generated, then the associated surface heat flux would be 2.24 +/- 0.45 W/square m. This estimate is in good agreement with observed global heat flow, but to better constrain tidal dissipation mechanisms and infer how thermal energy is transferred to Io's surface, it is critical to closely examine the spatial distribution of volcanic features. End-member tidal dissipation models either consider that heating occurs completely in the mantle, or completely in the asthenosphere. Mixed models typically favor one-third mantle and two-thirds asthenosphere heating. Recent models also consider the effects of mantle-asthenosphere boundary permeability and asthenospheric instabilities. Deep-mantle heating models predict maximum surface heat flux near the poles, whereas asthenosphere heating models predict maxima near the equator-particularly in the Sub-Jovian and Anti-Jovian hemispheres, with smaller maxima occurring at orbit tangent longitudes. Previous studies have examined the global distribution of Ionian hotspots and patera (i.e., irregular or complex craters with scalloped edges that are generally interpreted to be volcanic calderas), but in this study, we combine a new geospatial analysis technique with an improved hotspot and paterae database

Understanding GIC in the UK and French high-voltage transmission systems during severe magnetic storms

The measurement and collection of digital magnetic field data in Europe extends back to the 1970s, providing over 30 years of data for the analysis of severe space weather. Although paper records can potentially extend these data sets back by over a century, few digitized records are currently available for use in extreme studies. Therefore, we rely on theoretical arguments and modeling to elucidate the largest likely variations of the magnetic field. We assess the relationship, during the three largest storms in the digital era, between variations in the horizontal magnetic field and the largest measured Dst index to estimate likely magnetic variations for more extreme storms in northern and midlatitude Europe. We examine how geomagnetically induced currents (GIC) flow in the UK and French networks during recent severe storms and analyze the sensitivity of these flows to changes in grid parameters. The maximum GIC computed at any one node in the French and UK grids are 44 A and 208 A, respectively. Sensitivity tests show that while gross changes of the whole network structure, such as disconnecting parts of the network, reduces the mean GIC per node, changes in GIC at individual nodes have distinct behaviors implying that local effects are network dependent and require detailed modeling to sufficiently characterize GIC. In addition, the scale factors we have derived allow GIC results from recent storms to be upscaled to estimate the potential risk to the system from more extreme events, such as the Carrington storm in 1859

Evolution of Global Lightning in the Transition From Cold to Warm Phase Preceding Two Super El Niño Events

Multistation observations of Schumann resonance (SR) intensity document common behavior in the evolution of continental‐scale lightning activity in two super El Niño events, occurring in 1997/98 and 2015/16. The vertical electric field component of SR at Nagycenk, Hungary and the two horizontal magnetic field components in Rhode Island, USA in 1997, and in 2014–2015, the two horizontal magnetic field components at Hornsund, Svalbard and Eskdalemuir, United Kingdom as well as in Boulder Creek, California and Alberta, Canada exhibit considerable increases in SR intensity from some tens of percent up to a few hundred percents in the transition months preceding the two super El Niño events. The UT time distribution of anomalies in SR intensity indicates that in 1997 the lightning activity increases mainly in Southeast Asia, the Maritime Continent and India, i.e. the Asian chimney region. On the other hand, a global response in lightning is indicated by the anomalies in SR intensity in 2014 and 2015. SR‐based results are strengthened by comparison to independent lightning observations from the Optical Transient Detector and the World Wide Lightning Location Network, which also exhibit increased lightning activity in the transition months. The increased lightning is attributable to increased instability due to thermodynamic disequilibrium between the surface and the midtroposphere during the transition. The main conclusion is that variations in SR intensity may act as a precursor for the occurrence and magnitude of these extreme climate events, and in keeping with earlier findings, as a precursor to maxima in global surface air temperature. Schumann resonance (SR) is a global phenomenon produced by low frequency electromagnetic radiation (\u3c100 Hz) from worldwide lightning. Lightning strokes act as wideband electromagnetic antennas transmitting in this specific frequency band, and due to the extreme low attenuation of electromagnetic waves, their radiated signals can be observed anywhere on Earth. This phenomenon enables the monitoring of global lightning with just a very few (up to four in this study) observation sites around the globe. The main advantage of the SR‐based method is the expectation that all of the worldwide lightning contributes to the measured SR field, which means the absence of detection efficiency problems which are inherent with many other lightning detection methods. In this work, we use SR measurements to monitor changes in both regional and global lightning activity in connection with two extremely large magnitude, so called “super” El Niño events (1997/98 and 2015/16). Our conclusion is that SR intensity variations in the transition months preceding these two El Niño events indicate an important increase in lightning activity attributable to thermodynamic disequilibrium. We suggest that SR intensity variations might be applied in the future to predict the occurrence of these extreme climate events. Schumann resonance intensities are analyzed from distant stations in connection with two super El Niño events Increased Schumann resonance intensity indicates enhanced lightning activity in the transition from cold to warm phase in both events Schumann resonance intensity may be a precursor for occurrence of super El Niño events and for maxima in global surface air temperature Schumann resonance intensities are analyzed from distant stations in connection with two super El Niño events Increased Schumann resonance intensity indicates enhanced lightning activity in the transition from cold to warm phase in both events Schumann resonance intensity may be a precursor for occurrence of super El Niño events and for maxima in global surface air temperatur

Geomagnetic Virtual Observatories: monitoring geomagnetic secular variation with the Swarm satellites

We present geomagnetic main field and secular variation time series, at 300 equal-area distributed locations and at 490 km altitude, derived from magnetic field measurements collected by the three Swarm satellites. These Geomagnetic Virtual Observatory (GVO) series provide a convenient means to globally monitor and analyze long-term variations of the geomagnetic field from low-Earth orbit. The series are obtained by robust fits of local Cartesian potential field models to along-track and East–West sums and differences of Swarm satellite data collected within a radius of 700 km of the GVO locations during either 1-monthly or 4-monthly time windows. We describe two GVO data products: (1) ‘Observed Field’ GVO time series, where all observed sources contribute to the estimated values, without any data selection or correction, and (2) ‘Core Field’ GVO time series, where additional data selection is carried out, then de-noising schemes and epoch-by-epoch spherical harmonic analysis are applied to reduce contamination by magnetospheric and ionospheric signals. Secular variation series are provided as annual differences of the Core Field GVOs. We present examples of the resulting Swarm GVO series, assessing their quality through comparisons with ground observatories and geomagnetic field models. In benchmark comparisons with six high-quality mid-to-low latitude ground observatories we find the secular variation of the Core Field GVO field intensities, calculated using annual differences, agrees to an rms of 1.8 nT/yr and 1.2 nT/yr for the 1-monthly and 4-monthly versions, respectively. Regular sampling in space and time, and the availability of data error estimates, makes the GVO series well suited for users wishing to perform data assimilation studies of core dynamics, or to study long-period magnetospheric and ionospheric signals and their induced counterparts. The Swarm GVO time series will be regularly updated, approximately every four months, allowing ready access to the latest secular variation data from the Swarm satellites

Towards GIC forecasting: statistical downscaling of the geomagnetic field to improve geoelectric field forecasts

Geomagnetically induced currents (GICs) are an impact of space weather that can occur during periods of enhanced geomagnetic activity. GICs can enter into electrical power grids through earthed conductors, potentially causing network collapse through voltage instability or damaging transformers. It would be beneficial to power grid operators to have a forecast of GICs that could inform decision making on mitigating action. Long lead-time GIC forecasting requires magnetospheric models as drivers of geoelectric field models. However, estimation of the geoelectric field is sensitive to high-frequency geomagnetic field variations which operational global magneto-hydrodynamic models do not fully capture. Furthermore, an assessment of GIC forecast uncertainty would require a large ensemble of magnetospheric runs, which is computationally expensive. One solution that is widely used in climate science is “downscaling”, wherein sub-grid variations are added to model outputs on a statistical basis. We present proof-of-concept results for a method that temporally downscales low-resolution magnetic field data on a 1-hour timescale to 1-minute resolution, with the hope of improving subsequent geoelectric field magnitude estimates. An analogue ensemble (AnEn) approach is used to select similar hourly averages in a historical dataset, from which we separate the high-resolution perturbations to add to the hourly average values. We find that AnEn outperforms the benchmark linear-interpolation approach in its ability to accurately drive an impacts model, suggesting GIC forecasting would be improved. We evaluated the ability of AnEn to predict extreme events using the FSS, HSS, cost/loss analysis and BSS, finding that AnEn outperforms the “do-nothing” approach

Evaluation of candidate geomagnetic field models for IGRF-12

Background: The 12th revision of the International Geomagnetic Reference Field (IGRF) was issued in December 2014 by the International Association of Geomagnetism and Aeronomy (IAGA) Division V Working Group V-MOD (http://www.ngdc.noaa.gov/IAGA/vmod/igrf.html). This revision comprises new spherical harmonic main field models for epochs 2010.0 (DGRF-2010) and 2015.0 (IGRF-2015) and predictive linear secular variation for the interval 2015.0-2020.0 (SV-2010-2015). Findings: The models were derived from weighted averages of candidate models submitted by ten international teams. Teams were led by the British Geological Survey (UK), DTU Space (Denmark), ISTerre (France), IZMIRAN (Russia), NOAA/NGDC (USA), GFZ Potsdam (Germany), NASA/GSFC (USA), IPGP (France), LPG Nantes (France), and ETH Zurich (Switzerland). Each candidate model was carefully evaluated and compared to all other models and a mean model using well-defined statistical criteria in the spectral domain and maps in the physical space. These analyses were made to pinpoint both troublesome coefficients and the geographical regions where the candidate models most significantly differ. Some models showed clear deviation from other candidate models. However, a majority of the task force members appointed by IAGA thought that the differences were not sufficient to exclude models that were well documented and based on different techniques. Conclusions: The task force thus voted for and applied an iterative robust estimation scheme in space. In this paper, we report on the evaluations of the candidate models and provide details of the algorithm that was used to derive the IGRF-12 produc

Proliferative myositis of the Latissimus Dorsi presenting in a 20-year-old male athlete

We describe the case of a 20-year-old rower presenting with an uncommon condition of Proliferative Myositis (PM) affecting the Latissimus Dorsi (LD). PM is a rare, benign tumour infrequently developing in the upper back. Its rapid growth and firm consistency may mistake it for sarcoma at presentation. Therefore, careful multidisciplinary work-up is crucial, and should involve appropriate radiological and histopathological investigations. Here, we propose the aetiology of LD PM to be persistent myotrauma induced by repetitive rowing motions. Symptoms and rate of progression ultimately determine the management which includes surveillance and/or conservative resection. There have been no documented cases of recurrence or malignant transformation

Modeling geoelectric fields in Ireland and the UK for space weather applications

Geoelectric fields at the Earth’s surface caused by geomagnetic storms have the potential to disrupt and damage ground-based infrastructure such as electrical power distribution networks, pipelines, and railways. Here we model geoelectric fields in Ireland and the UK during both quiet and active time intervals of geomagnetic conditions using measurements from magnetic observatories and electromagnetic tensor relationships. The analysis focused on (1) defining periods of the magnetic field variations that are largely affected by the geomagnetic storms, between 30 and 30,000 s; (2) constraining the electromagnetic tensor relationships that defines the Earth’s response to magnetic field variations; (3) implementing and validating two approaches for modeling geoelectric fields based on measurements from magnetic observatories and local and interstation electromagnetic transfer functions; and (4) estimating uncertainties when modeling geoelectric fields. The use of interstation tensor relationships allowed us to differentiate between regional and local geomagnetic sources. We found coherence values of 0.5–0.95, signal-to-noise ratio of 1–15 dB, normalized root-mean-square values of 0.8–3.4, and root-mean-square values of 0.7–84 mV/km. Within these ranges of values, sites in close proximity (<100 km) to a magnetic observatory and not affected by local storms will provide the most accurate results, while sites located at further distances and affected by spatially localized features of the storm will be less accurate. These methods enable us to more accurately model geomagnetically induced currents, and their associated uncertainties, in the British and Irish power networks