Summary The British Geological Survey's global geomagnetic model, Model of the Earth's Magnetic Environment (MEME), is an important tool for calculating the strength and direction of the Earth's magnetic field, which is continually in flux. While the ability to collect data from ground‐based observation sites and satellites has grown rapidly, the memory bound nature of the original code has proved a significant limitation on the size of the modelling problem required. In this paper, we describe work done replacing the bespoke, sequential, eigensolver with that of the PETSc/SLEPc package for solving the system of normal equations. Adopting PETSc/SLEPc also required fundamental changes in how we built and distributed the data structures, and as such, we describe an approach for building symmetric matrices that provides good load balance and avoids the need for close coordination between the processes or replication of work. We also study the memory bound nature of the code from an irregular memory accesses perspective and combine detailed profiling with software cache prefetching to significantly optimise this. Performance and scaling characteristics are explored on ARCHER, a Cray XC30, where we achieved a speed up for the solver of 294 times by replacing the model's bespoke approach with SLEPc.

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.

The British Geological Survey (BGS) is responsible for the Swarm Level-2 fast-track magnetospheric field model product (MMA_SHA_2F), Quick-Look (MAG_QL and EFI_QL) and geomagnetic observatory data (AUX_OBS_2_) products and VALidation of many of the Level-2 CAT-1 products, as part of the consortium of institutes making up the Swarm Data, Innovation, and Science Cluster (DISC). We summarise these activities and provide updates on recent progress.

We describe the candidate models submitted by the British Geological Survey for the 12th generation International Geomagnetic Reference Field. These models are extracted from a spherical harmonic ‘parent model’ derived from vector and scalar magnetic field data from satellite and observatory sources. These data cover the period 2009.0 to 2014.7 and include measurements from the recently launched European Space Agency (ESA) Swarm satellite constellation. The parent model’s internal field time dependence for degrees 1 to 13 is represented by order 6 B-splines with knots at yearly intervals. The parent model’s degree 1 external field time dependence is described by periodic functions for the annual and semi-annual signals and by dependence on the 20-min Vector Magnetic Disturbance index. Signals induced by these external fields are also parameterized. Satellite data are weighted by spatial density and by two different noise estimators: (a) by standard deviation along segments of the satellite track and (b) a larger-scale noise estimator defined in terms of a measure of vector activity at the geographically closest magnetic observatories to the sample point. Forecasting of the magnetic field secular variation beyond the span of data is by advection of the main field using core surface flows.

The 12th generation of the International Geomagnetic Reference Field (IGRF) was adopted in December 2014 by the Working Group V-MOD appointed by the International Association of Geomagnetism and Aeronomy (IAGA). It updates the previous IGRF generation with a definitive main field model for epoch 2010.0, a main field model for epoch 2015.0, and a linear annual predictive secular variation model for 2015.0-2020.0. Here, we present the equations defining the IGRF model, provide the spherical harmonic coefficients, and provide maps of the magnetic declination, inclination, and total intensity for epoch 2015.0 and their predicted rates of change for 2015.0-2020.0. We also update the magnetic pole positions and discuss briefly the latest changes and possible future trends of the Earth’s magnetic field.

The International Geomagnetic Reference Field (IGRF) model is a reference main field magnetic model updated on a quinquennial basis. The latest revision (generation 12) was released in January 2015. The IGRF-12 consists of a definitive model (DGRF2010) of the main field for 2010.0, a model for the field at 2015.0 (IGRF2015) and a prediction of secular variation (IGRF-12 SV) for the forthcoming five years until 2020.0. The remaining coefficients of IGRF-12 are unchanged from IGRF-11. Nine candidates were submitted from various international teams for consideration to the IGRF Taskforce led by Erwan Thebault (Nantes) and Chris Finlay (DTU Space). The final models were computed from all candidates using a Huber weighting in space scheme. In this poster, we outline the modelling steps for the three BGS candidate models and compare them to the other submitted candidates and the final official models released as IGRF-12.

Over the past 20 years, directional borehole drilling has become increasingly important for improving the optimal extrac­tion of reserves from challenging targets and for reducing wellbore collisions. Very long wells drilled using borehole steering methods can take weeks to months to complete and rely on accurate models of the Earth’s magnetic field which necessarily include a parameterization of its time variation. Magnetic field models used in the hydrocarbon industry, such as the BGS Global Geomagnetic Model (BGGM), are computed from data collected by a network of ground-based magnetic observato­ries and from low Earth-orbiting satellites. Magnetic field models provide snapshots looking back in time, but to be useful to industry, they also need to predict how the field will change in the future. Previously, predictions of magnetic variation have been based on relatively simple extrapolation of the observed changes. We introduce a physics-based technique to forecast the changes in the field by deducing large-scale flow of the iron-rich liquid at the top of the outer core and use this to advect the present magnetic field forwards in time. We demonstrate that this method produces valuable improvements in the accuracy of magnetic field models and hence an improved tool for directional drilling.

We investigate the impact of early Swarm data on global magnetic field models. Since November 2013, Swarm has been providing satellite vector magnetic data, the first since the end of the CHAMP mission over three years ago. We describe two models of the Earth's magnetic field, one of which incorporates Swarm data. Both models include data from the CHAMP and Orsted satellites and from observatories. All data are similarly selected on the basis of local time, solar zenith angle, upstream solar wind conditions and magnetic activity. The different data are weighted according to their type, location and estimation of content of signal not being modelled. The time-varying large-scale magnetospheric field is co-estimated with the internal field. We also provide an update on efforts to collate and check ground-based observatory measurements in support of the Swarm mission. These are particularly important for bridging the gap between CHAMP and Swarm as they provide the only accurate vector observations of the magnetic field during that time.

The scientific use of Swarm data and Swarm-derived products is greatly enhanced through combination with observatory data and indices. The strength of observatory data is that they are very stable over long periods of time with great care being taken with temperature control and correction, platform stability and magnetic cleanliness at each site. As part of the Swarm Level-2 data activities, plans are in place to distribute such ground-based data along with the Swarm data as auxiliary data products. We describe here the preparation of the data set of ground observatory hourly mean values, including procedures to check and select observatory data spanning the modern magnetic survey satellite era. Existing collaborations, such as INTERMAGNET and the World Data Centres for Geomagnetism, are proving invaluable for this. In addition, we discuss other possible combined uses of satellite and observatory data. Quasi-definitive 1-second data are now available from a number of observatories worldwide. A preliminary study using Champ satellite data has shown that these observatory data could prove beneficial as a secondary tool for Swarm magnetic data validation; however, to avoid ionospheric and magnetospheric interference requires satellite-observatory crossings to occur during quiet, local night time. Whether or not such passes will transpire during the period of Swarm Calibration/Validation is highly dependent on the initial timing of orbital insertion and how active the magnetic field is. Alternatively, we consider exploiting 1-minute data, collected from a much larger global network of observatories. Removing an estimate of the main field from both the observatory and satellite observations during crossings could provide a baseline for detecting abnormalities and aid with Swarm measurement validation, whilst differences observed with solar zenith angle may constrain thermal fluctuations not otherwise accounted for. It is possible that early validation results with magnetic data from the Swarm mission will be presented if launch is successful in the preceding months.

Swarm, a three-satellite constellation to study the dynamics of the Earth’s magnetic field and its interactions with the Earth system, is expected to be launched in late 2013. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution, in order to gain new insights into the Earth system by improving our understanding of the Earth’s interior and environment. In order to derive advanced models of the geomagnetic field (and other higher-level data products) it is necessary to take explicit advantage of the constellation aspect of Swarm. The Swarm SCARF (SatelliteConstellationApplication andResearchFacility) has been established with the goal of deriving Level-2 products by combination of data from the three satellites, and of the various instruments. The present paper describes the Swarm input data products (Level-1b and auxiliary data) used by SCARF, the various processing chains of SCARF, and the Level-2 output data products determined by SCARF.

The BGS Global Geomagnetic Model (BGGM) is widely used by the oil industry as a reference magnetic field model for precision drilling of well bores. The BGGM is revised annually to keep pace with changes in the geomagnetic field and incorporates the most recent magnetic field measurements made at magnetic observatories and by satellite surveys. More than 3 million measurements are used to derive a model that captures field changes due to magnetic processes in the core, crust and in space. With 25 companies in the oil and gas sector subscribing to the BGGM the model is used daily at drilling locations around the world, from Alaska to Australia, helping to drill hundreds of wells every year accurately to reservoir targets, so ensuring efficient extraction of oil and gas resources. Accurate drilling also means that the risk of well collisions – drilling into a pre-existing well - can be properly managed. Additionally, using the Earth’s magnetic field for direction finding offers cost saving when compared to other technologies, without sacrificing accuracy. Where things go wrong, as in the Deepwater Horizon oil spill, the BGGM is used in drilling relief wells with the intention of approaching the problem well so that an intervention can be made. In many cases the BGS supplies values of local changes to the magnetic field caused by magnetised rocks, and estimates of real time changes, driven by the solar activity, as additional ‘refinements’ to the BGGM. With the launch of the three-satellite ESA SWARM magnetic survey mission in November 2013 new data will be accumulating steadily for several years, helping to improve future BGGM revisions. BGS is one of a consortium of European scientific institutions commissioned to deliver data products from the SWARM mission.

Magnetic field models are produced on behalf of the European Space Agency (ESA) by an independent scientific consortium known as the Swarm Satellite Constellation Application and Research Facility (SCARF), through the Level 2 Processor (L2PS). The consortium primarily produces magnetic field models for the core, lithosphere, ionosphere and magnetosphere. Typically, for each magnetic product, two magnetic field models are produced in separate chains using complementary data selection and processing techniques. Hence, the magnetic field models from the complementary processing chains will be similar but not identical. The final step in the overall L2PS therefore involves inspection and validation of the magnetic field models against each other and against data from (semi-) independent sources (e.g. ground observatories). We describe the validation steps for each magnetic field product and the comparison against independent datasets, and we show examples of the output of the validation. In addition, the L2PS also produces a daily set of ‘Quick Look’ output graphics and statistics to monitor the overall quality of Level 1b data issued by ESA. We describe the outputs of the ‘Quick Look’ chain.

Sophisticated space weather monitoring aims at nowcasting and predicting solar-terrestrial interactions because their effects on the ionosphere and upper atmosphere may seriously impact advanced technology. Operating alert infrastructures rely heavily on ground-based measurements and satellite observations of the solar and interplanetary conditions. New opportunities lie in the implementation of in-situ observations of the ionosphere and upper atmosphere onboard low Earth orbiting (LEO) satellites. The multi-satellite mission Swarm is equipped with several instruments which will observe electromagnetic and atmospheric parameters of the near Earth space environment. Taking advantage of the multi-disciplinary measurements and the mission constellation different Swarm products have been defined or demonstrate great potential for further development of novel space weather products. Examples are satellite based magnetic indices monitoring effects of the magnetospheric ring current or the polar electrojet, polar maps of ionospheric conductance and plasma convection, indicators of energy deposition like Poynting flux, or the prediction of post sunset equatorial plasma irregularities. Providing these products in timely manner will add significant value in monitoring present space weather and helping to predict the evolution of several magnetic and ionospheric events. Swarm will be a demonstrator mission for the valuable application of LEO satellite observations for space weather monitoring tools.

As part of the European Space Agency (ESA) Swarm mission, ESA has commissioned an independent scientific consortium known as the Swarm satellite Constellation Application and Research Facility (SCARF) to develop and operate the Level 2 Processor (L2PS). Its purpose is to derive high quality scientific products from the mission’s data. One such product is the Fast-Track Magnetospheric Model (FTMM), which is a model of the large scale vector magnetospheric field and its induced counterpart. This model is generated once per satellite orbit, in near real-time by a robust, autonomous algorithm. Its intended use is similar to that of the Disturbance storm time Index (Dst): characterising the rapidly varying magnetospheric field, as an input to other global field models, and for the space weather community. In this paper we describe in detail the FTMM algorithm and assess its ability to recover the magnetospheric component from the consortium’s test satellite data set as well as real data from the CHAMP satellite.