High-resolution temperature profiles retrieved from bichromatic stellar scintillation measurements by GOMOS/Envisat
Abstract. In this paper, we describe the inversion algorithm for retrievals of high
vertical resolution temperature profiles (HRTPs) using bichromatic stellar
scintillation measurements in the occultation geometry. This retrieval
algorithm has been improved with respect to nominal ESA processing and
applied to the measurements by Global Ozone Monitoring by Occultation of
Stars (GOMOS) operated on board Envisat in 2002–2012. The retrieval method
exploits the chromatic refraction in the Earth's atmosphere. The
bichromatic scintillations allow the determination of the refractive angle,
which is proportional to the time delay between the photometer signals. The
paper discusses the basic principle and detailed inversion algorithm for
reconstruction of high-resolution density, pressure and temperature profiles
in the stratosphere from scintillation measurements. The HRTPs are
retrieved with a very good vertical resolution of ∼200  m and
high precision (random uncertainty) of ∼1 –3 K for altitudes
of 15–32 km and with a global coverage. The best accuracy is achieved for
in-orbital-plane occultations, and the precision weakly depends on star
brightness. The whole GOMOS dataset has been processed with the improved
HRTP inversion algorithm using the FMI's scientific processor; and the
dataset (HRTP FSP v1) is in open access. The validation of small-scale fluctuations in the retrieved HRTPs is
performed via comparison of vertical wavenumber spectra of temperature
fluctuations in HRTPs and in collocated radiosonde data. We found that the
spectral features of temperature fluctuations are very similar in HRTPs and
collocated radiosonde temperature profiles. HRTPs can be assimilated into atmospheric models, used in studies of
stratospheric clouds and used for the analysis of internal gravity waves' activity. As an example of geophysical applications, gravity wave potential
energy has been estimated using the HRTP dataset. The obtained
spatiotemporal distributions of gravity wave energy are in good agreement
with the previous analyses using other measurements.