Malina, E; Yoshida, Y; Matsunaga, T; Muller, J-P; (2018) Information content analysis: the potential for methane isotopologue retrieval from GOSAT-2. Atmospheric Measurement Techniques Discussions , 11 (2) pp. 1159-1179. 10.5194/amt-11-1159-2018.

Preview	Text (Final revised paper) Muller_Information content analysis. The potential for methane isotopologue retrieval from GOSAT 2_VoR.pdf - Published Version Download (16MB) | Preview
Preview	Text (Discussion paper) Muller_Information content analysis. The potential for methane isotopologue retrieval from GOSAT 2_AAM.pdf - Accepted Version Download (14MB) | Preview

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.

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