Methane and carbon dioxide retrievals from airborne and space-borne observations in the short-wave infrared

Abstract

This research presents our progress in the retrieval of methane (CH4) and carbon dioxide (CO2) concentrations on both small (local, regional) and large (global) scales using short-wave infrared (SWIR) observations, leveraging advanced computational tools and validated algorithms. Our approach builds upon Py4CAtS (Python for Computational Atmospheric Spectroscopy), a Python-based implementation of GARLIC (Generic Atmospheric Radiative Transfer Line-by-line Infrared Code) coupled with BIRRA (Beer InfraRed Retrieval Algorithm). Recently, BIRRA-GARLIC has been successfully validated using ground-based measurements from TCCON (Total Carbon Column Observing Network) and NDACC (Network for the Detection of Atmospheric Composition Change). The software suite BIRRA-Py4CAtS utilizes line data from latest spectroscopic databases such as the SEOM-IAS (Scientific Exploitation of Operational Missions- Improved Atmospheric Spectroscopy) and includes parameterizations for Rayleigh and aerosol extinction. Furthermore, the latest version of Py4CAtS accounts for continuum absorption using collision-induced absorption (CIA) and supports various analytical and tabulated instrument spectral response functions. The progess and findings contribute to our understanding of greenhouse gas distribution on local and global scales, crucial for studying climate change and its impacts.