|Paper title||Methane and carbon dioxide retrievals from airborne and space borne observations in the short-wave infrared|
|Form of presentation||Poster|
We present our latest results towards the retrieval of methane (CH4) and carbon dioxide (CO2) concentrations on small (local) and large scales using short-wave infrared (SWIR) observations from airborne and space borne sensors.
The code developments are based on Py4CAtS (Python for Computational Atmospheric Spectroscopy), a Python reimplementation of GARLIC, the Generic Atmospheric Radiative Transfer Line-by-line Infrared Code coupled to BIRRA (Beer InfraRed Retrieval Algorithm). BIRRA-GARLIC has recently been validated with TCCON (Total Carbon Column Observing Network) and NDACC (Network for the Detection of Atmospheric Composition Change) ground based measurements.
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 parameterization for Rayleigh and aerosol extinction. Moreover, the latest Py4CAtS version accounts for continuum absorption by means of collision induced absorption (CIA) and facilitates a wide variety of analytical and tabulated instrument spectral response functions. Current developments of the inverse solver BIRRA are directed towards the physical approximation of atmospheric scattering and co-retrieval of effective scattering parameters in order to account for light path modifications when estimating small scale CO2 or CH4 variations.
Methane retrieval results are shown for SWIR observations acquired on a local scale by an airborne HySpex sensor during the CoMet (CO2 and Methane, see Atm. Meas. Tech. special issue) campaign. The retrieval of carbon dioxide is assessed with GOSAT (Greenhouse Gases Observing Satellite) observations. Synthetic/simulated spectra are examined to study the sensitivity of various retrieval setups.