The MATS satellite: Limb image data processing and calibration
Journal article, 2025

MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is a Swedish satellite mission designed to investigate atmospheric gravity waves. In order to observe wave patterns, MATS observes structures in the O2 atmospheric band airglow (light emitted by oxygen molecules in the mesosphere and lower thermosphere), as well as structures in noctilucent clouds (NLCs) which form around the mesopause. The main instrument is a telescope that continuously captures high-resolution images of the atmospheric limb. Using tomographic analysis of the acquired images, the MATS mission can reconstruct waves in three dimensions and provide a comprehensive global map of the properties of gravity waves. The data provided by the MATS satellite will thus be three-dimensional fields of airglow and NLC properties in 200 km-wide (across track) strips along the orbit at altitudes of 70 to 110 km. By adding spectroscopic analysis, by separating light into six distinct wavelength channels, it also becomes possible to derive temperature and microphysical NLC properties. Based on those data fields, further analysis will yield gravity wave parameters, such as the wavelengths, amplitudes, phase, and direction of the waves, on a global scale. The MATS satellite, funded by the Swedish National Space Agency, was launched in November 2022 into a 580 km sun-synchronous orbit with a 17.25 local time of the ascending node (LTAN). This paper accompanies the public release of the Level 1b (v. 1.0) dataset from the MATS limb imager. The purpose of the paper is to provide background information in order to assist users to correctly and efficiently handle the data. As such, it details the image processing and how instrumental artefacts are handled. It also describes the calibration efforts that have been carried out on the basis of laboratory and in-flight observations, and it discusses uncertainties that affect the dataset.

Author

L. Megner

Stockholm University

J. Gumbel

Stockholm University

Ole Martin Christensen

Stockholm University

Björn Linder

Stockholm University

Donal Murtagh

Chalmers, Space, Earth and Environment, Geoscience and Remote Sensing

N. Ivchenko

Royal Institute of Technology (KTH)

Lukas Krasauskas

Stockholm University

Jonas Hedin

Stockholm University

Joachim Dillner

Stockholm University

G. Giono

Royal Institute of Technology (KTH)

G. Olentšenko

Royal Institute of Technology (KTH)

Louis Kern

Stockholm University

Joakim Möller

Molflow AB

Ida Sofia Skyman

Molflow AB

J. Stegman

Stockholm University

Atmospheric Measurement Techniques

1867-1381 (ISSN) 1867-8548 (eISSN)

Vol. 18 22 6869-6892

MATS 2018-2021 at Chalmers

(299/17), 2018-01-01 -- 2021-12-31.

Subject Categories (SSIF 2025)

Meteorology and Atmospheric Sciences

DOI

10.5194/amt-18-6869-2025

More information

Latest update

12/2/2025