Information content analysis: the potential for methane isotopologue retrieval from GOSAT-2

Abstract

Abstract. Atmospheric methane is comprised of multiple isotopic molecules, with the most abundant being 12CH4 and 13CH4, making up 98 and 1.1 % of atmospheric methane respectively. It has been shown that is it possible to distinguish between sources of methane (biogenic methane, e.g. marshland, or abiogenic methane, e.g. fracking) via a ratio of these main methane isotopologues, otherwise known as the δ13C value. δ13C values typically range between −10 and −80 ‰, with abiogenic sources closer to zero and biogenic sources showing more negative values. Initially, we suggest that a δ13C difference of 10 ‰ is sufficient, in order to differentiate between methane source types, based on this we derive that a precision of 0.2 ppbv on 13CH4 retrievals may achieve the target δ13C variance. Using an application of the well-established information content analysis (ICA) technique for assumed clear-sky conditions, this paper shows that using a combination of the shortwave infrared (SWIR) bands on the planned Greenhouse gases Observing SATellite (GOSAT-2) mission, 13CH4 can be measured with sufficient information content to a precision of between 0.7 and 1.2 ppbv from a single sounding (assuming a total column average value of 19.14 ppbv), which can then be reduced to the target precision through spatial and temporal averaging techniques. We therefore suggest that GOSAT-2 can be used to differentiate between methane source types. We find that large unconstrained covariance matrices are required in order to achieve sufficient information content, while the solar zenith angle has limited impact on the information content.