Calibration/Validation Efforts for Magnetospheric Plasma Sensor – Low Energy, the New Plasma Instrument Onboard NOAA’s GOES-16/-17 Satellites

The Space Environment In-Situ Suite (SEISS) on NOAA’s GOES-16/-17 satellites includes a new instrument for measuring low-energy plasma populations, the Magnetospheric Particle Sensor – Low Energy (MPS-LO). MPS-LO is comprised of four electrostatic analyzers that measure electrons and ions in 15 energy (E/q) channels between 0.03 and 30 keV, in 12 unique look directions. The first MPS-LO on GOES-16 has been returning real time data since January 8, 2017, and the second one on GOES-17 has been operating in real time since April 24, 2018. Extensive calibration/validation activities have been performed for both instruments to ensure instrument health and data quality. Here we discuss three major issues that have been investigated: (1) Contamination of the MPS-LO electron and proton channels by penetrating medium-energy electrons. The medium-to-high-energy electron population is monitored by the Magnetospheric Particle Sensor – High Energy (MPS-HI) instrument, also onboard the GOES spacecraft. The MPS-HI electron channels cover the energy range 50 keV – 4 MeV. Various quantitative analyses have been performed, pointing to high correlations between the MPS-LO backgrounds and the MPS-HI 600-800 keV electron populations. The mechanism for the contamination by these medium energies is still unknown. (2) Presence of negative electron and proton fluxes after the removal of backgrounds. The MPS-LO backgrounds are measured independently through 4 “background” channels not illuminated by the instrument aperture. Subtraction of the unscaled backgrounds from the in-band fluxes sometimes leads to negative fluxes. An empirical scheme has been developed to remove weighted background levels as to avoid negative fluxes. The background removal coefficients are calculated through this scheme for a specific time period, and are applied to accurately determine the true in-band fluxes. (3) Long term analysis of the in-band and background rates reveal a downward trend of both with time. It is the in-band rates, however, that decrease more rapidly leading to varying background removal coefficients with time, as calculated from the above technique. The source of the gradual decline in rates is still under investigation.