RUSSIAN JOURNAL OF EARTH SCIENCES, VOL. 18, ES4003, doi:10.2205/2018ES000626, 2018
A. Soloviev, Sh. Bogoutdinov, S. Agayan, R. Redmon, T. M. Loto'aniu, H. J. Singer
As a part of the space environment monitor instrument suite, Geostationary Operational Environmental Satellite carries two boom-mounted magnetometers that measure the local magnetic field vector with a 0.5 second sampling rate. These data contain occasional baseline perturbations not of geophysical origin. One source of contamination is due to switching heaters that are installed along with each magnetometer and used to stabilize the temperature of the instrument. Detection of the heater induced field is complicated by the fact that in most cases these jumps are so small that they are hard to distinguish visually. In the present work we have developed the algorithm JM (from JUMP) aimed at automated and uniform recognition of jumps in GOES 2 Hz vector magnetic measurements. We present the performance of the JM algorithm to a full day of measurements on 3 April 2010. On this date, almost all jumps were recognized by the JM algorithm. The results demonstrate that the algorithm might be used to improve the existing data set from GOES 13, 14 and 15 series, and perhaps find use with the next generation of GOES satellites, beginning with GOES 16 launched on 19 November 2016.
Received 15 May 2018; accepted 2 July 2018; published 25 August 2018.
Citation: Soloviev A., Sh. Bogoutdinov, S. Agayan, R. Redmon, T. M. Loto'aniu, H. J. Singer (2018), Automated recognition of jumps in GOES satellite magnetic data, Russ. J. Earth Sci., 18, ES4003, doi:10.2205/2018ES000626.
Copyright 2018 by the Geophysical Center RAS.