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

Malina, Edward; Yoshida, Yukio; Matsunaga, Tsuneo; Muller, Jan-Peter

Atmospheric methane is comprised of multiple isotopic molecules, with the most abundant being inline-formula12CHinline-formula4 and inline-formula13CHinline-formula4, 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 inline-formulaδ13C value. inline-formulaδ13C values typically range between inline-formula−10 and inline-formula−80 ‰, with abiogenic sources closer to zero and biogenic sources showing more negative values. Initially, we suggest that a inline-formulaδ13C 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 inline-formula13CHinline-formula4 retrievals may achieve the target inline-formulaδ13C 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, inline-formula13CHinline-formula4 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.



Malina, Edward / Yoshida, Yukio / Matsunaga, Tsuneo / et al: Information content analysis: the potential for methane isotopologue retrieval from GOSAT-2. 2018. Copernicus Publications.


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