GAFS Geomagnetic Activity Forecast a Service for Prospectors

GAFS : Geomagnetic Activity Forecast – a Service for Prospectors and Surveyors J. Watermann (1), H. Gleisner (1), T. Rasmussen (2), S. Mc. Culloch (3) (1) (2) (3) Danish Meteorological Institute, Copenhagen, Denmark Geological Survey of Denmark and Greenland, Copenhagen, Denmark formerly Baker Hughes INTEQ Scandinavia – now Halliburton Noway, Sperry Drilling Services Synthesis Methodology The project objective has been the development of a computer-based system for a targeted geomagnetic activity forecast service. The service consists of a brief description of observed solar activity and current and expected geomagnetic activity at selected sites together with a graphical scheme displaying the level of disturbance of the geomagnetic field expected over the next three hours, the next 12 hours and the next two days. The geomagnetic disturbance level is scaled according to the geographic area – sub-auroral, auroral and polar cap latitudes – and according to specific user requirements. The service is provided automatically and continously. A number of empirical models relating geomagnetic activity to the solar-wind conditions have been presented in the scientific literature. Using real-time solar wind data from the ACE spacecraft as input to a filter, e. g. a linear/nonlinear filter or a neural network, short-range geomagnetic forecasts (an hour ahead, although in GAFS this range is extended to 3 hours) can be made. In GAFS, we use a linear filter whose input consists of parameters that are non-linear functions of fundamental solar-wind observables. Automatically updated forecasts are presented in detail on a restricted Web site, and a summary of expected activity levels appear on the publicly accessible web site http: //www. dmi. dk/projects/ESA_SWAPP/Public/magoutlook. shtml Project manager: Jurgen Watermann (jfw@dmi. dk) Danish Meteorological Institute Atmosphere Space Research Division To go beyond a lead time of a few hours requires that we incorporate remote observations of the solar surface and the inner heliosphere into our forecast scheme. The solar sources of geomagnetic activity can schematically be separated into transient eruptive events and quasi-static recurrent structures roughly co-rotating with the Sun. In GAFS, we use earth-directed halo Coronal Mass Ejections (CMEs) – observed by the LASCO instrument onboard the SOHO spacecraft and with interpretations provided by the NRL – as the primary indicator of potentially geoeffective solar-wind disturbances over the next few days. From the fluxes of Solar Energetic Particles (SEPs) observed by the SEM instrument onboard the GOES geostationary satellites, the expected geoeffectiveness is quantified an appropriate alert level is defined. In the absence of solar eruptive events we assume that the solar wind is governed by large-scale, quasi-static solar magnetic fields co-rotating with the Sun. Based on observations of solar surface magnetic fields, solarwind models currently provide forecasts of solar wind velocity and the magnitude and direction of the interplanetary magnetic field. From a statistical relationship between geomagnetic activity and the boundaries between low-speed and high-speed solar wind streams and IMF sectors, and using the solar wind forecasts provided by solar wind models, we forecast moderate geomagnetic activity beyond the short-range time scale of a few hours. The primary data sets which we use as input to our scheme can be organized into four categories: Background The geomagnetic field is at all times subject to temporal variations on a wide range of time scales. They originate in solar activity and solar variability of many different forms including solar flares, coronal mass ejections, solar wind sector boundaries and coronal hole streams. The figure below (left) gives an example of geomagnetic variations of large amplitude observed during a severe (but not extreme) geomagnetic storm at three sites located on the east and west coasts of Greenland, respectively (below right). The stations are neighbours in the sense that no other magnetometers were in operation in between them. The magnetic variations shown in the figure are uncorrelated. It is therefore not possible to apply a-posteriori corrections for magnetic field variations to those measurements which were taken at a place somewhere in between these stations. Such conditions prohibit spatial interpolation between neighboring sites and render simultaneous measurements from remote reference stations useless. • remote sensing of the sun and solar corona data sources: SOHO spacecraft and ground-based solar observatories - modeled solar wind speed and interplanetary magnetic field direction data sources: Hakamada-akasofu-Fry (HAF) solar wind model data • in-situ sensing of the solar wind and interplanetary magnetic field data sources: ACE and SOHO spacecraft • in-situ sensing of solar X-ray and energetic proton flux in the magnetosphere data sources: GOES satellites • in-situ sensing of the magnetic variations at ground level data sources: DMI ground-based magnetometers However, under different conditions the spatial correlation of geomagnetic variations can be much larger, and it is worth-while interpolating between spaced observations in order to estimate the local perturbation. GAFS project scheme The flow diagram outlines the structure and the elements of the prediction scheme. The left hand column lists the input data sources, the central blocks summarize the elements of the prediction algorithm which are currently under development by the service provider (DMI), and the blocks on the right hand side show the expected output product designed for the service users (GEUS and Baker Hughes INTEQ). Figure 1 left: total geomagnetic field variations during a strong but not extreme storm (Dst – 109) right: sites where the observations were collected Figure 3 Variations of such intensity can adversely affect any technical system which relies on local magnetic field measurements to be taken in the absence of significant geomagnetic variations. Users who are unaware of and thus unprepared for the imminent occurrence of major magnetic field disturbances may conduct operations which later turn out to have been useless and eventually a waste of time and resources. The project will include a performance analysis, prediction versus observation, and an assessment of the costs potentially being saved through the use of our geomagnetic activity forecast service. Summaries of the forecast and the performance evaluation will be made available on our publicly accessible web site. Data flow and geomagnetic activity forecast algorithms employed in the project Our project attempts to address this problem through the development of a service which gives advance notice of increasing geomagnetic activity and thus enables the potentially affected users to plan and conduct their operations in a more cost-effective way. The project strives to address specifically the needs of • oil companies which perform directional drilling controlled by magnetic field sensors close to the borehead • magnetic survey enterprises which map magnetostatic anomalies for geological research and prospection Figure 4 Publicly accessible project web site showing a two-day forecast of magnetic activity for the areas of Denmark and Greenland The figure below shows the result from an aeromagnetic survey conducted in 1998 in an area at the west coast of Greenland (see section indicated by an arrow). The local magnetostatic deviations from the geomagnetic reference field span about 1000 n. T peak-to-peak. In this example, the spatial magnetic field variations reach the same order of magnetic as the storm-time temporal variations displayed in the figure above. Under these conditions it is obviously not possible to conduct an aeromagnetic survey which can render useful measurements. Times during which magnetic storms are in progress have therefore to be avoided, I. e. , no survey flights should be scheduled. The future of the forecast service Figure 5 Figure 2 Sample results from a magnetostatic anomaly survey carrtied out in southwest Greenland. The color scale indicates a total field span of ca 1000 n. T between minimum and maximum. Theoretically possible levels of user demands and service maintenance options