Can we intercalibrate satellite measurements by means of data
assimilation? An attempt on LEO satellites
Abstract
Low Earth Orbit (LEO) satellites offer extensive data of the radiation
belt region, but utilizing these observations is challenging due to
potential contamination and difficulty of intercalibration with
spacecraft measurements at Highly Elliptic Orbit (HEO) that can observe
all equatorial pitch-angles. This study introduces a new
intercalibration method for satellite measurements of energetic
electrons in the radiation belts using a data assimilation approach. We
demonstrate our technique by intercalibrating the electron flux
measurements of the National Oceanic and Atmospheric Administration
(NOAA) Polar-orbiting Operational Environmental Satellites (POES)
NOAA-15,-16,-17,-18,-19 and MetOp-02 against Van Allen Probes
observations from October 2012 to September 2013. We use a reanalysis of
the radiation belts obtained by assimilating Van Allen Probes and
Geostationary Operational Environmental Satellites (GOES) observations
into 3-D Versatile Electron Radiation Belt (VERB-3D) code simulations
via a standard Kalman filter. We compare the reanalysis to the POES
dataset and estimate the flux ratios at each time, location and energy.
From these ratios we derive energy and $L^*$ dependent
recalibration coefficients. To validate our results, we analyse on-orbit
conjunctions between POES and Van Allen Probes. The conjunction
recalibration coefficients and the data-assimilative estimated
coefficients show strong agreement, indicating that the differences
between POES and Van Allen Probes observations remain within a factor of
two. Additionally, the use of data assimilation allows for improved
statistics, as the possible comparisons are considerably increased.
Data-assimilative intercalibration of satellite observations is an
efficient approach that enables intercalibration of large datasets using
short periods of data.