The DSCOVR Solar Wind Mission: Algorithm Development to Enhance Space Weather Forecasting

Abstract:

We present two space weather algorithms currently under development for use with the upcoming DSCOVR solar wind mission. DSCOVR, which will orbit the L1 Lagrangian point, will provide real-time solar wind thermal plasma and magnetic field measurements to ensure continuous monitoring for space weather forecasting. The DSCOVR spacecraft will include a Faraday cup to measure the proton and alpha particle components of the solar wind and a triaxial fluxgate magnetometer to measure the magnetic field in three dimensions. In preparation for the launch of DSCOVR in January 2015, algorithm development is currently underway for the first two space weather products designed to enhance space weather forecasting.

The first algorithm is an improvement to computing the L1 to Earth delay time. The standard technique for propagating the solar wind from L1 to Earth assumes that all observed solar wind discontinuities, such as interplanetary shocks and ICME boundaries, are in a flat plane perpendicular to the Sun-Earth line traveling in the GSE X direction at the solar wind velocity. In reality, these phase plane fronts can have significantly tilted orientations, and thus relying on a ballistic propagation method often results in delay time errors ranging from 15 minutes to over 30 minutes depending on the distance between the solar wind monitoring spacecraft and the Sun-Earth line. The L1 to Earth delay time product presented here is designed to more accurately predict the delay time from DSCOVR to Earth by taking these tilted phase plane fronts into account.

The second algorithm being developed is an automated solar wind regime identification product, which is designed to autonomously identify the type of solar wind flow in which the monitoring spacecraft is currently situated. This algorithm takes into account the proton speed, density, temperature, and alpha particle abundance and uses a logic-based binary decision tree to determine whether the solar-wind source is most likely a coronal hole, interstream flow, or a coronal mass ejection. An automated shock detection algorithm is included as part of the solar wind regime identification product and recent work to determine the optimal set of shock detection criteria to use with DSCOVR will also be presented.