Towards MTG-IRS retrieval of CO using IASI from the interferogram domain

Onboard of MetOp satellite series, Infrared Atmospheric Sounding Interferometer (IASI) is a Fourier Transform spectrometer based on the Michelson interferometer. IASI acquires interferograms from which high-resolution atmospheric emission spectra are provided, enabling the derivation of temperature and humidity profiles (among other parameters) with exceptional spectral resolution. In this study, we will use the IASI archive to evaluate a retrieval approach in the interferogram domain, which we anticipate will be well-suited for near-real-time (NRT) analysis of extensive spectral datasets expected from next-generation tropospheric sounders like MTG-IRS. The Partially Scanned Interferograms (PSI) method, applied to the retrieval of trace gases from IASI, has only rarely been studied. However, existing studies suggest its potential for specific gases, including CO, CO₂, CH₄, and N₂O, which could enable highly accurate trace gas column density retrievals at the resolution of a single IASI footprint.

We will present the interferogram retrieval approach of CO from IASI simulations. These results are based on the set of simulations of IASI interferograms for which the identified regions (optical path differences), sensitive to the carbon monoxide species, are noised and then used for retrievals. Furthermore, the study which aims to compare the performance of the interferogram retrieval approach compared to the conventional (i.e. from the spectral domain) will also be presented. The expected advantage compared to the usual methods is an efficient use of the information contained in all IASI channels that are available in the absorption bands of a specific gas species. Finally, using interferogram points sensitive to parameters of interest, we will also present a proof of concept of a neural network algorithm for classification of the interferograms predicting the surface temperature and the abundance of H₂O and CO.

The simulation of IASI spectra was conducted using the LATMOS Atmospheric Retrieval Algorithm (LARA), a robust and validated radiative transfer model based on Least Squares estimation [Segonne et al., 2021]. The climatological library TIGR [Chédin et al., 1985; Chevallier et al., 1998] was used to generate IASI interferograms with LARA. TIGR comprises 2311 atmospheric scenarios, each characterized by temperature, water vapor, and ozone concentration values across a specified pressure grid from the surface to the top of the atmosphere. The study focuses on carbon monoxide, a key trace gas for understanding air quality and climate forcing. Carbon monoxide exhibits a characteristic “comb” absorption pattern within the 2050–2350 cm⁻¹ wavenumber range [Serio et al., 2012]. Simulations were performed for surface temperatures ranging from -15 to +15 K, in 5 K increments from the base temperature, to assess the impact of thermal contrast [Baudin et al., 2016]. Additionally, the study explores the potential of correlating interferogram characteristics with surface temperature and H₂O content, aiming to enhance the accuracy of CO column retrievals.