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

Project EURISGIC : worst case scenarios (technical note D5.1)

The overall objective of Work Package 5 of the EURISGIC project (see website eurisgic.eu) is defined as being: “Estimate the largest possible GIC flowing anywhere in the European high-voltage power grid, based on archive data.” This document is a technical note (deliverable item D5.1) for the results of this work package. For each of the project team members participating in the work package (FMI – Finland; Neurospace – Sweden; IRF – Sweden; NASA and Catholic University of America - USA; BGS - UK) we summarise activities related to worst case scenario modelling: activities such as research into extreme event statistical methods, theoretical extreme event modelling and individual (historical and hypothetical) event studies. We note that research is continuing and therefore some results reported here are subject to further confirmation in published scientific journals

Recent BGS activities for the Swarm DISC

The British Geological Survey is responsible for the fast-track magnetospheric field model product (MMA_SHA_2F), geomagnetic observatory data (AUX_OBS*2_) products and Level 2 CAT-1 product validation, as part of the consortium of institutes making up the Swarm Expert Support Laboratory. We summarise these activities and provide updates since the Living Planet Symposium in June 2016. The fast-track magnetospheric field model product is generated automatically and disseminated on a daily basis after receipt of the Swarm L1b files. With more than three years of accumulated models, we comment on the longer-term behaviour of the magnetospheric field. The observatory hourly-mean (AUX_OBS_2_) data product is updated every 3 months using a selection of definitive and quasi-definitive data from observatories around the world. Since Swarm was launched, good quality data from about 120 observatories are available. BGS started issuing new observatory data products in October 2016 with a 4-day lag. Regular updates are made if new data are found. These products consist of 1-second observatory (AUX_OBSS2_) and 1-minute (AUX_OBSM2_) quasi-definitive data from the start of the Swarm mission, and are made available on the BGS anonymous FTP server at ftp://ftp.nerc-murchison.ac.uk/geomag/Swarm/AUX_OBS/. A summary of temporal and spatial coverage of all observatory data products is provided. Validation of the Level 2 CAT-1 products comprises comparisons of the Swarm-based models to independent models and data where possible, and inter-comparisons of models from the dedicated and comprehensive processing chains. A selection of plots from recent validation reports is given

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

On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting

Space weather represents a severe threat to ground-based infrastructure, satellites and communications. Accurately forecasting when such threats are likely (e.g., when we may see large induced currents) will help to mitigate the societal and financial costs. In recent years computational models have been created that can forecast hazardous intervals, however they generally use post-processed “science” solar wind data from upstream of the Earth. In this work we investigate the quality and continuity of the data that are available in Near-Real-Time (NRT) from the Advanced Composition Explorer and Deep Space Climate Observatory (DSCOVR) spacecraft. In general, the data available in NRT corresponds well with post-processed data, however there are three main areas of concern: greater short-term variability in the NRT data, occasional anomalous values and frequent data gaps. Some space weather models are able to compensate for these issues if they are also present in the data used to fit (or train) the model, while others will require extra checks to be implemented in order to produce high quality forecasts. We find that the DSCOVR NRT data are generally more continuous, though they have been available for small fraction of a solar cycle and therefore DSCOVR has experienced a limited range of solar wind conditions. We find that short gaps are the most common, and are most frequently found in the plasma data. To maximize forecast availability we suggest the implementation of limited interpolation if possible, for example, for gaps of 5 min or less, which could increase the fraction of valid input data considerably